This article investigates the performance of various sophisticated channel coding and transmission schemes for achieving reliable transmission of a highly compressed video stream. Novel error protection schemes including Non-Convergent Coding (NCC) scheme, Non-Convergent Coding assisted with Differential Space Time Spreading (DSTS) and Sphere Packing (SP) modulation (NCDSTS-SP) scheme and Convergent Coding assisted with DSTS and SP modulation (CDSTS-SP) are analyzed using Bit Error Ratio (BER) and Peak Signal to Noise Ratio (PSNR) performance metrics. Furthermore, error reduction is achieved using sophisticated transceiver comprising SP modulation technique assisted by Differential Space Time Spreading. The performance of the iterative Soft Bit Source Decoding (SBSD) in combination with channel codes is analyzed using various error protection setups by allocating consistent overall bit-rate budget. Additionally, the iterative behavior of SBSD assisted RSC decoder is analyzed with the aid of Extrinsic Information Transfer (EXIT) Chart in order to analyze the achievable turbo cliff of the iterative decoding process. The subjective and objective video quality performance of the proposed error protection schemes is analyzed while employing H.264 advanced video coding and H.265 high efficient video coding standards, while utilizing diverse video sequences having different resolution, motion and dynamism. It was observed that in the presence of noisy channel the low resolution videos outperforms its high resolution counterparts. Furthermore, it was observed that the performance of video sequence with low motion contents and dynamism outperforms relative to video sequence with high motion contents and dynamism. More specifically, it is observed that while utilizing H.265 video coding standard, the Non-Convergent Coding assisted with DSTS and SP modulation scheme with enhanced transmission mechanism results in  Video on-demand transmission is the major factor of the estimated increase in network traffic over the cellular network. By the end of 2023, the emerging increase in mobile applications downloading will reach 300 million and the 5G speeds will reach about 575 Mbps, which is 13 times higher than the average mobile connections. There will be a significant need in increase of bandwidth with the highest connectivity requirements of the future networks. A crucial factor leading the increase in mobile speed is the increasing proportion of 4G mobile connection and the rising interest in 5G connections [For a raw video sequence with one pixel representation of a gray scale and color video, 8 and 24 bits are used correspondingly. A total of 944 Mbps is required to display one frame of a simple colored TV video with a resolution of 1024 × 768 pixels with a frame rate of 25 fps [For the very first time, Shannon proposed the basics of channel capacity bounds over a noisy channel providing minimum probability of errors by employing complex encoding systems and identified the error-resilient features of the communication systems ,7. ShannAuthors in ,26,27,28A delightful source coding candidate for wireless video communication is the compression efficient standard H.264 ,38,39,40Taking in mind the above background, we propose an arrangement for the H.264 and HEVC compressed video bitstream transmission through Soft Bit Source Decoding (SBSD) scheme. The propose system uses H.264 and H.265  as a souH.264 and H.265 source compression standard has been incorporated in order to visualize the quality of the highly compressed video stream at the receiver.SP modulation are included in order to observe the performance of the proposed systems on fading channel.SP modulation is inspired by space time modulation and provides the diversity and coding gain for the proposed system in order to efficiently estimate and recover the actual transmitted information.DSTS scheme is included to remove the Channel State Information (CSI) estimation dependency and the receiver does not required to know the channel fade.Different inner and outer code rates are used in the concerned schemes to visualize the effect of code rates on the convergence property of iterative schemes.EXIT chart are used for finding the number of profitable iterations in the decoding process.Diverse video sequences have been tested to measure the role of the static objects having fine details, dynamism and motion of the object in the background, on the performance metrics.To the best of our knowledge, this is distinctive research study to transmit the highest compression efficient coded video using the H.265/HEVC standard while employing the advocated wireless transmission setup.The following is the main contributions of the proposed work while considered in designing of the three systems i.e., NCC, NCDSTS-SP and CDSTS-SP:The rest of the proposed manuscript has been structured as follows. In MIMO schemes are mainly used for multiplexing and diversity gain. In multiplexing, different uncorrelated symbols are transmitted from all the antennas while for providing diversity gain, the transmitted symbols should be correlated. Space Time Block Codes (STBC) performs encoding both in space domain as well as in time domain due to using two transmitting (Tx) antennas and requiring two period for transmitting the information symbols. The first Tx antenna transmit the original symbol and all the remaining Tx antennas are transmitting the linear combination or the conjugate version of the symbol that are transmitting from the first antennas. In case of two Tx antennas, symbols ented as :[d1−d2∗dt using differential PSK from the constellation are:From the decoding matrix, the column contains the symbols transmitted at the corresponding time period while the rows comprises of the symbols transmitted from the specific Tx antenna. STBC with the following encoding matrix was proposed for four Tx antennas .(1)12·[s follow :(3)[dt+1The design criteria that guarantee maximum diversity and coding gain can be find , e.g., tequation .(4)rsigN Tx antennas over the total duration of T time period transmission is given below.Here, the codeword is expressed with Equation  between T time period of transmission with a total of M receiving antennas is expressed as in the following equation.At the receiving side, the signal for a If the antennas are far away then the path gain is independent from each other, otherwise a spatial correlation exist that can be expressed with the following An error occurred if codeword L number of codewords is given below:The probability of error using the union bound for a set of comprising H is conjugate and transpose a the corresponding matrix.For an error matrix e define  in term M receiving antennas, i.e., the power of SNR  ,51.The Alamouti code is a full rank matrix and is satisfies the determinant criteria. Considering a time correlated Rayleigh fading channel, SP modulation obtaining a full diversity gain using the joint combination of orthogonal designs with sphere packing . Let, then below ,53:(15)GFurthermore, the SP signals are constructed using the above equation as expressed in the following equation.The symbol rate is denote as Equation , the setUsing the same Equation , the setThe differential MIMO (DSTS) scheme comprises two encoders i.e., differential encoder and space time spreading (STS) encoder as shown in equation .(20)ddiAfter passing from the STS encoder, the two consecutive symbols at both the transmitting antennas is expressed with the following mapping as shown in Typically, the primitive of the transmitter block comprises discrete input, encoder, digital modulator, and the output. Channel encoder is operating for the removal of error effects by adding some redundancy through a controlled methodology in the information bits. Channel flexibility takes place by manipulating RSC codes as a constituent channel codes to efficiently operate in AWGN and as well in Rayleigh fading channels. The preliminaries and system design criteria has been briefly explained in . The proParameter set structure, containing sharable information deployed in the decoding process. The new Video Parameter Set (VPS) is based on the concepts of sequence and picture parameter sets used in H.264.Network Abstraction Layer (NAL) unit is retained which is helpful in identification of the purpose of payload data.In case of data losses, synchronization is done in H.265 with the help of slices. The same concept of slices is followed in H.264.Information about the timing of a video picture, interpretation of the color space and other display related information is provided by Supplemental Enhancement Information (SEI) and Video usability Information (VUI) metadata, adopted in H.265 and H.264.Advance Video Coding (AVC)/H.264 is a compression standard resulted in the extension of the video service delivery to various networks and applications. The coding architecture of H.264 consists of two basics layers i.e., Video Coding Layer (VCL) and Network Adaptation Layer (NAL). VCL provided efficient representation of video contents while NAL provides network friendly representation. On the other hand, HEVC is the latest state of the art video compression standard designed for achieving the goals of parallel-processing, resilience to data-loss and coding efficiency . It compThe hybrid approach of standard H.261 concerning inter/intra-prediction and 2D transform is also imported in H.265. A prediction residual is computed based on the inter-picture motion compensation or intra-picture spatial predictions. This residual undergoes through block transformation, quantization and entropy coding respectively. A detailed description can be found in ,56,58.HEVC fulfilled the target 50% compression efficiency improvement over the predecessor H.264/AVC, providing adequate image quality with the trade-off computational complexity. HEVC consumes half bandwidth to that of the AVC thats why users experiences a reasonable video quality over very small bandwidth. The standard is specifically designed to be compatible with all the existing applications of the previous codecs.Furthermore, HEVC divides each frame into slices where slice is a sequence of an independent and subsequent dependent slice segments. Each slice has a specific header that enables its independent decoding of all the other slices in a given picture. Slice segments comprises of Coding Tree Units (CTU) which contains one luma and two chroma Code Tree Block (CTB) along with their syntax while CTB is a region of N × N  samples of the image, with the fact that larger sizes provide better compression. The higher size of the CTB is largely required when higher resolution videos are to be encoding which is beneficial for reducing the decoding time. Similarly, CTB can be further divided into coding blocks (CB), one luma CB and two Chroma CB along with syntax are called coding unit (CU). The size of CB should be in the range of 8 × 8 ≤ CB Size ≤ CTB size. The CTB blocks are then further divided into Transform Blocks (TB) for Discrete Cosine Transform (DCT) into a block of 4 × 4 and similarly the luma TBs and two chroma TBs combine along with their syntax to form Transform Unit (TU). For example, HEVC divides the frame into two slices while the first slice comprises three slice segments refer to The compressed video bit-stream comprises three partitions types A, B, and C of all the slices per frame. The bit-stream The encoded bit-stream received from the source channel encoding block is then forwarded to modulation and transmission block. Using NCC scheme the received bit-stream is mapped to the stream of QPSK symbols. Afterwards, the Single Input Single Output (SISO) transmitter antenna is used to transmit the QPSK modulated Symbols over Rayleigh Fading channels.L is the modulated symbols that represents the number of SP signaling elements [While using NCDSTS-SP and CDSTS-SP schemes the received bit-stream is mapped to the SP symbols elements ,60. AfteDSTS transceiver is liable to diversity gain in wireless network, reduced BER and accomplished a substantial video quality improvement. Due to embedding DSTS MIMO scheme, the proposed transceivers can be deployed in diverse environment for providing better video quality performance.At the decoder side the received signal is first presented to the DSTS decoder and SP demapper which gives the Log-Likelihood Ratios (LLRs) value for the bit-stream. The generated LLR values are forwarded to the next block for further processing.K-bit sequence on transmission of Subsequently, the extrinsic LLRs information received from the modulation and transmission block is then exchanged between the RSC decoders and SBSD in iterative fashion. The extrinsic information for Markov zero order model using SBSD can be found in . The resEventually, the channel output information is combined with the A-priori knowledge of that corresponding symbol to achieve the resultant LLR extrinsic value, as expressed below.Natural redundancy residue in the encoded bit stream EXIT chart operates on the special property of iterative decoder, which is convergence behavior as proposed by Stephen ten Brink , by explained in ,27,28. TMoreover, the EXIT curve for NCC scheme of SBSD using OCM rate-1 inner code and RSC rate-1/3 outer code is shown in This section provides a detailed performance analysis of the proposed system. The JM version 15 video and HM master codec developed by the joint video team (JVT) is used as a reference H.264 and H.265 source encoder. The proposed systems is simulated using IT++ signal processing and communications library, coded in C++. To perform a fair analysis between the three schemes, several aspects of the proposed systems have been considered. Various sample of the diverse video sequences is considered and provided as an input to the considered system models. Convergence behavior in iterative source channel decoding is specifically analyzed in the proposed work with different code rates of the inner and outer channel codes. In our simulation, three different video sequences—i.e., AKIYO, FOREMAN and MOBILE as shown in Akiyo: This is a video of newscaster with extremely negligible movement and less details in the background.Foreman: This is a video of a foreman with rapidly moving face, extensive zoom out, average details and regular structures.Mobile: This is a video of a moving toy train with high details and dynamism.Brief information about the video sequences used in the simulation experiments is as follows:The idea of using these different diverse video sequences with different video resolutions, level of motion and dynamism is to investigate the impact of video contents on its objective video quality while considering similar channel. As the extent of compression and robustness of the coded bit-stream is directly linked with its resolution, dynamism and motion content of the video stream, therefore the objective video quality performance of different video sequences is expected to be variable, while considering similar communication setup.The number of bits per frame for luminance and chrominance in different sampling format and video sequences are calculated from  as depicIn order to reduce the computational complexity, iterations between RSC and SBSD decoders are set to 3 and 5 for the OCM rate-1 and The measurement of video quality is a major task in a scenario where there is a transmission of a compressed video over noisy channels. Subjective  and objeX having dimension of size Y can be expressed by the following equation.X and can be calculated as B bits per sample.PSNR is the ratio between the signal of the power of the original signal to that of the corrupted signal. PSNR is traditionally used as a quality metric for evaluating algorithms in multimedia streaming systems. It is generally expressed in term of Mean Square Error (MSE). The MSE of an image The BER and PSNR performance of the simulation work were plotted against varying In our simulation scenarios OCM is employed as inner code, while RSC is used as outer channel code. Furthermore, in the considered NCC scheme QPSK modulation is employed, while in NCDSTS-SP and CDSTS-SP sphere packing modulation is used in combination with DSTS.Furthermore, in order to analyze the impact of varying motion contents and dynamism of video scene on the objective video quality performance of the transmission scheme, its PSNR versus In order to analyze the impact of varying video resolution on the objective video quality performance of the transmission scheme its PSNR versus The BER versus The effects of BER on PSNR performance of the CDSTS-SP scheme can be easily observed from Eb/N0 performance of the three advocated schemes—i.e., NCC, NCDSTS-SP and CDSTS-SP with reference to the employed H.264 and H.265 standards is presented in The PSNR Vs Eb/N0 gain of 20 dB with reference to the NCC coding and transmission mechanism at the objective PSNR value of 42 dB. It is important to mention that both NCC and NCDSTS-SP schemes have employed identical code rate. Furthermore, the CDSTS-SP with convergent coding mechanism achieved superior performance with reference to the equivalent rate NCDSTS-SP counterpart mechanism, with a performance gain of 16 dB at the objective PSNR grade of 42 dB. Moreover, it is observed that the maximum achievable PSNR gain through H.265 video coding standard is 45 dB, with a PSNR gain of 3 dB with reference to the identical code rate H.264 coding scheme. Furthermore, it is observed from that the BER and PSNR versus This paper presents performance analysis of sophisticated channel coding and transmission schemes for reliable transmission of H.264/AVC and H.265/HEVC compressed video. Three different coding and transmission schemes were presented, namely Non-Convergent Coding (NCC), Non-Convergent Coding assisted with Differential Space Time Spreading (DSTS) and Sphere Packing (SP) modulation (NCDSTS-SP) and Convergent Coding assisted with Differential Space Time Spreading (DSTS) and Sphere Packing (SP) modulation (CDSTS-SP). Different diverse combination of source mapping techniques and channel coding techniques were employed and their convergence behavior is analyzed with the aid of Extrinsic Information Transfer (EXIT) Charts. Furthermore, to improve the diversity gain of the transceiver advanced Sphere Packing (SP) modulation technique assisted by Differential Space Time Spreading (DSTS) is employed. The BER and PSNR performance of the proposed schemes were plotted against varying


This paper deals with the impact of content on the perceived video quality evaluated using the subjective Absolute Category Rating (ACR) method. The assessment was conducted on eight types of video sequences with diverse content obtained from the SJTU dataset. The sequences were encoded at 5 different constant bitrates in two widely video compression standards H.264/AVC and H.265/HEVC at Full HD and Ultra HD resolutions, which means 160 annotated video sequences were created. The length of Group of Pictures (GOP) was set to half the framerate value, as is typical for video intended for transmission over a noisy communication channel. The evaluation was performed in two laboratories: one situated at the University of Zilina, and the second at the VSB—Technical University in Ostrava. The results acquired in both laboratories reached/showed a high correlation. Notwithstanding the fact that the sequences with low Spatial Information (SI) and Temporal Information (TI) values reached better Mean Opinion Score (MOS) score than the sequences with higher SI and TI values, these two parameters are not sufficient for scene description, and this domain should be the subject of further research. The evaluation results led us to the conclusion that it is unnecessary to use the H.265/HEVC codec for compression of Full HD sequences and the compression efficiency of the H.265 codec by the Ultra HD resolution reaches the compression efficiency of both codecs by the Full HD resolution. This paper also includes the recommendations for minimum bitrate thresholds at which the video sequences at both resolutions retain good and fair subjectively perceived quality. In recent years, the number of various types of surveillance and data collection cameras located both indoors and outdoors have been constantly increasing. Popularity of home security cameras is also growing as even high-quality models become more affordable. Typical surveillance cameras applications include public safety, protection of facilities against theft or vandalism, remote video monitoring, traffic surveillance, weather monitoring, or more special cases, such as animal monitoring or data collection, for statistical or marketing purposes. Today, due to the pandemic situation, face recognition with and without a protective mask is also becoming a point of interest for researchers in cooperation with technology companies ,2,3. It i-th row, and j-th column of n-th frame in time [For our measurements, we used the dataset from the Media Lab of the Shanghai Jiao Tang University . We sele in time . Both of in time  and plotIn our research, we decided to explore the quality of 8-bit video sequences at two commonly used resolutions, i.e., Full HD (FHD) and Ultra HD (UHD) with a typical chroma subsampled YUV 4:2:0 format. Because original sequences were uncompressed and YUV 4:4:4 color format at Ultra HD resolution with 10-bit depth was used, we had to convert them to the appropriate formats. Therefore, all test sequences were first chroma subsampled from YUV 4:4:4 to YUV 4:2:0 format and also the bit depth was changed from 10 to 8 bits per channel. Subsequently, all these conversion steps were repeated for Full HD resolution utilizing the FFmpeg tool . As we wffmpeg -i Wood_1920x1080_30fps_420_8bit_YUV.yuv -vcodec libx264 -command example-params keyint=15:min-keyint=15:bframes=3:b-adapt=1:bitrate=1000:vbv-maxrate=1000:vbv-bufsize=1000 Wood_1920x1080_30fps_420_8bit_H264_01M.mp4.All these test video sequences (SRCs) were afterwards encoded to both compression standards to be evaluated, i.e., H.264/AVC and H.265/HEVC. As a quality restriction parameter, we decided to use the constant bitrate. We selected 5 various target bitrates: 1, 3, 5, 10 and 15 Mbps based on our previous research  which haDuring the subjective testing, all created PVSs were shown to people of different ages and genders to evaluate their quality. We decided to use the Absolute Category Rating (ACR) method ,63 whichThirty participants, mostly students, were involved in the testing in each laboratory. All of them were naive observers which means they had no expertise in the image artefacts that may be introduced by the system under test. Naturally, they were thoroughly acquainted with the method of assessment, types of impairment, grading scale, sequence, and timing as required by Reference . The staAfter performing the subjective tests, we processed all collected results statistically; for each test sequence, codec, and resolution, the Mean Opinion Score (MOS) and 95 percent Confidence Interval (CI) in accordance with Reference  were calTo compare the MOS values obtained from both laboratories, i.e., from UNIZA and VŠB, and, to find out the correlation, the Pearson correlation coefficient (PCC), as well the Root Mean Square Error (RMSE) were calculated. All computations were done for both codecs and resolutions, as well as for all test sequences. The results are plotted in As we can see from at low bitrates—with increasing bitrate, the perceived quality rises, too, and approaches the perceived quality of sequences with low SI-TI values,at Ultra HD resolution rather than at Full HD resolution, andat H.265 codec rather than at H.264 codec.It is apparent from the graphs that the sequences with the lowest SI and TI values, such as the “Bund Nightscape” and the “Construction Field”, reached the best MOS value. Vice versa, the observers rated the sequences situated in the middle of the SI-TI diagram, such as the “Marathon” or “Runners”, as of worst quality. Interesting cases are the “Campfire Party” and the “Fountains” sequences. The “Campfire Party” contains a lot of movement  but not many details  and reached low MOS value, while the “Fountains” sequence lies near to the “Bund Nightscape” and the “Construction Field” sequences, meaning it has low both TI and SI values and also scored low on the MOS scale. A special case is the “Wood” sequence which is situated at the upper right corner of the SI-TI diagram. Nevertheless, its quality was perceived as similar to the sequences “Fountains” and “Runners”. All these differences are more pronounced:Based on these results, we can state that the compression efficiency and related video quality depends on the content of the sequences. However, the sequence representation and description only by the spatial and temporal information is not sufficient and should be the subject of further research. We suggest other parameters should be used to describe the scene, such as, for instance, the luminance and contrast or the colors occurring in the scene. In addition, the psychological factors should be considered. Based on the results, we can also state that the temporal information has greater impact on the perceived quality than the number of the objects defined by the spatial information.F-value, also called the F-ratio is calculated as the variance of the group means divided by the mean of the within group variances (Mean Squared Error). Greater F-value indicates more significant variation. In ANOVA, the p-value, i.e., the probability of getting the observed result at random, is also determined. For the source of variation to be regarded as insignificant, the p-value must be higher than a given alpha level, commonly set to 0.05. When performing ANOVA, the p-value is also determined to investigate the probability of rejecting the hypothesis.To verify what stemmed from the graphical representation of the subjective evaluation results, the ANOVA was applied on the data . The thrp-values.Based on the analysis of the tables, the following conclusions can be drawn. In We can draw several conclusions from Indisputably, the conclusions drawn from the Analysis of Variance (ANOVA) and the graphical representation of the subjective quality evaluation results coincide. These findings could be beneficial for visual media content providers and broadcasting companies, as they indicate how to adjust video compression parameters to improve its quality. The fastest growth of perceived video quality is apparently due to an increase in bitrate. Specifically, the quality increases most rapidly until the bitrate reaches a value of approximately 5 Mbps. The analyses also revealed which combination of resolution and compression format is best used so that the resulting quality of visual content is perceived by viewers as good as possible.Finally, From This paper dealt with the content impact on the perceived video quality evaluated using the subjective Absolute Category Rating (ACR) method. Eight types of video sequences with various scene content were evaluated. Two widely used video compression standards H.264/AVC and H.265/HEVC in combination with Full HD and Ultra HD resolutions, were tested. In the coding process, we selected 5 various bitrates based on our previous research, which showed that the efficiency of codecs grows nonlinearly with increasing bitrate. The number of bitrates was a compromise between the complexity and time requirements of subjective testing. In total, we created an annotated database which contains 160 different video sequences coded at constant bitrates with GOP set to half of the framerate value which is typical for video intended for transfer over a noisy communication channel. The perceived quality of the sequences was evaluated employing the subjective ACR method. The assessment was conducted in two laboratories: one situated at the University of Zilina, and the second at the VSB—Technical University in Ostrava. First, we calculated the correlation of the MOS values between both laboratories using the Pearson correlation coefficient (PCC) and the Root Mean Square Error (RMSE). The correlation proved to be considerably high. After that, we described the impact of the bitrate on video quality depending on scene content defined by Spatial (SI) and Temporal information (TI). The results showed that even if the sequences with low SI and TI values reach better MOS than the sequences with higher SI and TI values, these two parameters are not sufficient for scene description, and this domain should be the subject of further research. Subsequently, we described the impact of bitrate on video quality depending on codec and resolution. Based on the results, we concluded that the employment of the H.265 codec for compression of Full HD sequences is inessential, as the people did not observe any significant differences. Furthermore, we stated that the compression efficiency of the H.265 codec by the Ultra HD resolution reaches the compression efficiency of both codecs by the Full HD resolution. We also applied the ANOVA to verify what stemmed from the graphical representation of the subjective evaluation results. Finally, we determined the minimum bitrate thresholds at which the video sequences at both resolutions retain good and fair subjectively perceived quality.


Adjusting for all variables, the use of video-based communication was associated with less loneliness  and higher quality of life  among participants aged 60–69 years, while no associations were observed for participants in the oldest age group. The use of video-based communication tools was therefore associated with favorable psychological outcomes among participants in their sixties, but not among participants in the oldest age group. The study results support the notion that age may influence the association between the use of video-based communication tools and psychological outcomes amongst older people.The aim of the study was to examine the use of video-based communication and its association with loneliness, mental health and quality of life in older adults (60–69 years versus 70+ years) during the COVID-19 pandemic. A cross-sectional online survey was conducted in Norway, UK, USA and Australia during April/May 2020, and 836 participants in the relevant age groups were included in the analysis. Multiple regression analyses were conducted to examine associations between the use of video-based communication tools and loneliness, mental health and quality of life within age groups, while adjusting by sociodemographic variables. Video-based communication tools were found to be more often used among participants aged 60–69 years (60.1%), compared to participants aged 70 or above (51.8%,  Current video-based communication tools use an internet connection to allow users to communicate in real-time and see each other while doing so. In recent years, several such tools have also been developed to enable digital sharing of materials between the persons taking part in the call. Thus, video-based communication tools can greatly enhance the possibilities for exchange as well as the general communication experience, in comparison to regular telephone calls. While the first video-based communication system was launched by AT&T  in 1964 [With the onset of the global COVID-19 pandemic in March 2020, many countries experienced a lockdown. People were generally instructed to practice ‘social distancing’ . FlightsBefore the pandemic outbreak, substantial research had addressed elevated levels of loneliness and its relationship to mental health and quality of life in older people ,11,12. FNotwithstanding the potential of such technologies to reduce social and health inequities ,17, and In view of the literature review above, those in the oldest age group may have a particularly restricted social life due to COVID-19. Thus, their use of video-based communication tools may have the potential to protect against loneliness and promote mental health and quality of life. However, poorer ICT competence and familiarity among the oldest may hinder the realization of this potential. Explorative research on the associations between the use of video-based communication and psychological outcomes in different age groups is therefore warranted. Increased knowledge in this area may inform healthcare workers, policymakers, and the general public about the role of video-based communication tools among older people.The aim of this study was to examine the use of video-based communication and its association with loneliness, mental health, and quality of life in older adults aged 60–69 years versus 70+ years during the COVID-19 pandemic.An invitation to participate in this self-administered survey was distributed via different social media in Norway, USA, UK and Australia during April and May 2020 ,27. A naSociodemographic variables included age group (60–69 years versus 70 years and above), sex , highest completed education level , cohabitation (living with spouse or partner versus not), and employment status (having full-time or part-time employment versus not).The participants were asked to indicate (yes versus no) whether they used any of the following video-based communication platforms: FaceTime , Skype , Zoom , and Teams . A categorical variable was created to distinguish between those who used at least one of these video-based communication platforms, and those who did not.The Loneliness Scale  consistsThe General Health Questionnaire 12 (GHQ-12) is widely used as a self-report measure of mental health ,32. A laCantril’s ladder (CL) is a self-administered overall quality of life (QoL) questionnaire with one question, “How is your life”, asking the person to rate his or her present experience of life on a scale anchored by their own identified values . The rest-tests. Adjusted associations between independent variables and each of the outcome variables  were assessed with multiple linear regression analyses. Within each of the two age groups, ratings on the outcome variables were assessed in relationship to use or non-use of video-based communication platforms, while adjusting by sex, education level, cohabitation and employment status. Initial regression analyses also included the interaction term ‘video-based communication × country’ to assess whether associations between the use of video-based communications and the outcome variables differed by country. If the interaction term was not statistically significant, it was removed prior to the final analysis. In cases of statistically significant interactions, the analyses were repeated for each country separately. All independent variables were included in one step. Statistical significance was set at p < 0.05.Group proportions within sex, education level, cohabitation, employment status and use of video-based communications were compared by Chi-Square tests. Ratings on loneliness, mental health and quality of life were compared between participants in the two age groups by independent The data in this cross-sectional and cross-country study were collected anonymously. All ethical rules were followed in each country. The study was thereby quality assured and approved by OsloMet (20/03676) and the regional committees for medical and health research ethics  in Norway, reviewed by the University of Michigan Institutional Review Board for Health Sciences and Behavioral Sciences (IRB HSBS) and designated as exempt (HUM00180296) in the USA, by University Health Research Ethics (HSR1920-080) in the UK and by (HSR1920-0802020000956) in Australia.n = 93, 11.1%), USA , UK  and Australia , and the larger proportion was aged 60–69 years . The majority (75.7%) were women, and 70.2% had education at the bachelor’s degree level or higher. Among those aged 60–69 years (n = 612), full-time or part-time employment was held among 47.7%. Among those aged 70 years or more (n = 224), having employment was less common . The use of video-based communication was more common among those aged 60–69 (60.1%), compared to those in the oldest age group .The characteristics of the sample are displayed in M = 15.1 versus M = 14.2, respectively, p = 0.05) bordered on statistical significance. For loneliness and QoL, the differences were not statistically significant.p < 0.05). In all other analyses, the interaction term was not statistically significant and therefore removed. The results from the regression analyses are displayed in Adjustments were made for gender, education, employment and cohabitation status, and possible interactions between video-based communication and country were tested in initial models. Only one of the interaction terms was statistically significant, indicating that among those aged 70 or above, the association between video-based communication and quality of life differed between the four countries  and higher QoL ratings . In the whole sample, among participants aged 70 years or older, use of video-based communication platforms was not significantly associated with any of the outcome measures. In the country-specific analyses, the associations between these variables were found to be both positive  and negative (in Norway and USA), but they were not statistically significant for any of the countries.Among participants aged 60–69 years, use of video-based communication platforms was associated with lower ratings of loneliness .This study examined the use of video-based communication and its association with loneliness, mental health and quality of life in older adults between two different age groups (60–69 years versus 70 years or above) during the COVID-19 pandemic. In summary, more than half of the participants in both groups used video communication, with the older group using video communication less often. Among those aged 70 or more, the use of video-based communications was not related to any of the psychological outcomes. Among those aged 60–69 years, in contrast, the use of video-based communication was significantly related to lower loneliness and higher quality of life, although with small effect sizes. Overall, while levels of loneliness and mental health problems were elevated, in comparison to pre-pandemic studies ,40, therVideo-based communication was used by more than half of the participants in each age group but was used by a bigger proportion of those aged 60–69, compared to their older counterparts. The generally frequent use of video-based communication tools in both age groups may be interpreted as a reflection of the recruitment procedure. Recruitment by social media may have skewed the sample towards having more participants who are familiar with ICTs in general, including the use of video-based communication tools. However, the lower proportion of participants in the oldest age group using video-based communication tools may reflect the findings in prior studies ,15,16, sIn addition, a higher proportion of the 60–69 age group were still in employment compared to the 70 and older group, which may also account for the differences in use of video-based tools. With the onset of COVID-19, the use of video-based communication tools, such as Skype and Zoom, increased radically ,5, and aAmong those aged 70 years or older, the study showed no significant associations between use of video-based communications and any of the psychological outcome measures. In other words, their variations in loneliness, mental health and quality of life were not dependent on whether they used video-based communications. Thus, our findings support the view presented by Noone and co-workers , essentiAmong the oldest participants, it could also be that video-based contact needs to be initiated by family members such as children and grandchildren. In support of this reasoning, a qualitative study from Norway found that the sample of very old persons (median age 90.5 years) were predominantly “passive” users of video-based communication solutions  . This maAmong those aged 60–69 years, using video-based communication tools was significantly associated with lower loneliness and better quality of life. Among participants in this group, almost 50% still had full-time or part-time employment. Therefore, the association might partly reflect that employed participants were able to use video-based tools to connect with their colleagues, students, collaborators and work partners in job-related activities, which in turn might protect against a sense of loneliness and reduced quality of life. For those in employment, regular video-based job meetings might contribute to cover their need for contact with people outside of their own household. Thus, their use of video-based communication tools may be logically related to better quality of life and less loneliness.In comparison to the oldest participants, it could also be that participants who were in their sixties would be more comfortable with using ICTs in general ,15,16 anThe study was a sub-study of a larger cross-national comparative survey concerned with the impact of social distancing on mental health and quality of life during the early stages of the COVID-19 outbreak ,27. RecrMoreover, we did not collect data concerned with the participants’ competence and familiarity with the technologies used in video-based communication. Nor did we collect data on how such communication occurred, how often, for how long, with whom and with what purpose. Thus, several interesting aspects related to video-based communication among older people were not elucidated by our study.Following the result of a significant interaction between video-based communication and quality of life among those aged 70 years or older, the sample size of participants in this age group may have been too small to detect significant associations when rerunning the analyses by country. There may be differences between countries because of different social distancing policies in place, with mental health consequences, to protect older adults as they are at a higher risk of severe consequences if they get infected with COVID-19. Future studies in this field of research may preferably ascertain sufficient group sizes to enable the investigation of whether associations vary between countries. They may also assess, more specifically, the details of video-based communication practice, i.e., how often, with whom and for what purposes they were used .The comparisons were between participants in two different age-groups. About 50% of the respondents in the 60–69 age group were still in work, and we wondered if this might have impacted on our results. A recent systematic review of general population studies found that employment protected against mental distress during the early stage of the pandemic . While tThis study examined the use of video-based communication and its association with loneliness, mental health and quality of life among older adults during the COVID-19 pandemic. A larger proportion of participants aged 60–69 years used video-based communication tools, compared to those aged 70 years or above. Using such tools was associated with less loneliness and higher quality of life among participants in their sixties, whereas no significant associations were found among participants in the oldest age group. The study results support the notion that age may influence the association between use of video-based communication tools and psychological outcomes amongst older people, whereas the nature of this influence was in contrast to findings in previous research. While differences in the use of video-based communication likely concern more work participation among participants aged 60–69 years, less familiarity with ICTs and possibly a stronger inclination to disregard their value among persons in the oldest age group may more likely explain the age-dependent associations between video-based communication and psychological outcomes.


A clinical diagnosis of tic disorder involves several complex processes, among which observation and evaluation of patient behavior usually require considerable time and effective cooperation between the doctor and the patient. The existing assessment scale has been simplified into qualitative and quantitative assessments of movements and sound twitches over a certain period, but it must still be completed manually. Therefore, we attempt to find an automatic method for detecting tic movement to assist in diagnosis and evaluation. Based on real clinical data, we propose a deep learning architecture that combines both unsupervised and supervised learning methods and learns features from videos for tic motion detection. The model is trained using leave-one-subject-out cross-validation for both binary and multiclass classification tasks. For these tasks, the model reaches average recognition precisions of 86.33% and 86.26% and recalls of 77.07% and 78.78%, respectively. The visualization of features learned from the unsupervised stage indicates the distinguishability of the two types of tics and the nontic. Further evaluation results suggest its potential clinical application for auxiliary diagnoses and evaluations of treatment effects. Tourette syndrome (TS) is a childhood-onset neurodevelopmental disorder characterized by the presence of fluctuating motor and vocal tics . The corRecently, artificial intelligence and machine learning have been widely applied in the medical field. In particular, the development of video-based human motion behavior analysis technology has advanced various types of medical diagnoses, such as Parkinson's disease , seizureTic movements can be distributed throughout the body. Rickard's research  showed tIn recent decades, many studies have focused on the pathology, genetics, and clinical treatment of TS –16, but From these perspectives, we instead adapt a two-stage architecture by first training an unsupervised feature extraction model to make full use of the more easily acquired unlabeled data and then applying a comparatively simple network attached to the former trained model for the classification tasks. Visualizing the feature representation of the labeled data shows the correspondence with the tic parts, indicating that the unsupervised model learned the valid feature representation. This approach results in the following contributions: (1) we employ a deep learning scheme by a convolutional-neural-network- (CNN-) based model to learn feature representation from abundant unlabeled video data, (2) we apply a long short-term memory neural network (LSTM) to classify the feature sequences of video clips, and (3) an automated video-based system for detecting tic movements in TS patients is devised.To solve the problem of insufficient labeled data but enough monitoring video data, we propose a two-stage framework that combines unsupervised and supervised learning, as shown in Sixty-eight patients (4–13 years old) diagnosed with TS by two experienced specialists were employed in this study. All participants were inpatients under normal treatment recruited from the Second Affiliated Hospital of Zhejiang University School of Medicine between May and September 2019. This study was approved by the ethics committee of the Second Affiliated Hospital of Zhejiang University School of Medicine (YAN2019-148). All participants provided written informed consent with the agreement to participate in the study.The TS dataset was sourced from the Department of Pediatrics at the Second Affiliated Hospital of Zhejiang University School of Medicine and was collected using EEG video acquisition equipment installed in the pediatric ward. The video data were recorded in two situations: (i) the patient was asked to sit on a chair in front of the camera and (ii) before or after EEG recording, the patient was asked to agree to video recording. The two situations arise because the data were collected in different periods: (i) represents data collected during the preproject preparation phase, whereas (ii) is a part of the routine during subsequent EEG video recording. In both situations, every patient was informed in advance of the recording period and asked to face the camera as much as possible during recording, but no mandatory measures were imposed; the patients could move freely, which may result in useless frames. The patients' parents provided informed permission for the collection procedure and research use of the video recordings.https://github.com/microsoft/VoTT), which then generated annotated JavaScript Object Notation (JSON) files for postprocessing to extract annotations. The annotation work was independently performed by two clinicians and verified by the third expert, and they performed an extra check if there were disagreements until they reached a consensus. Finally, we cut and categorized the videos based on the timestamped annotations to form the TS research dataset, which can be supplemented at any time. We also segmented the video segments between two labeled tic events in the original video, which can be used as normal recordings and act as negative samples.Due to different camera devices, the original video frame rate includes video acquired at both 30 and 25 fps. The duration of all videos ranges from 5 to 15 minutes, and all the videos have a resolution of 1920 × 1080. The length of the videos is listed in There are more than five types of tics involving different muscle groups in the labeled data. The most common tics are eye tic and mouth tic. Not only in this research dataset but also most in clinical practice, these two tic types are widespread from a specialist's perspective . TherefoThe proposed method is composed of two stages, and there are slight differences in data preprocessing for the two stages. The common operation is to obtain the region of interest (ROI), which is defined as the area centered on the patient's face. This ensures that the models will focus on features related to patients' tic behaviors rather than on other family members or physicians visible in the videos. Identifying the ROI also reduces interference from different camera angles and from patient movements since they are free to move out of the camera view. This procedure uses a neural-network-driven face detection method. We use the multitask cascaded CNN (MTCNN)  architecThe difference between the two main stages during data preprocessing is that the first stage uses a relatively large number of frames from an unlabeled video dataset. As well known, the information between continuous video frames is usually highly redundant, which can cause overfitting during training. Thus, we perform a 3-fold downsampling procedure, which extracts the first frame for every three consecutive frames on the original videos. In the second supervised training stage, we first cut the original continuous video data into video segments and divide them into motion tic categories based on annotations. Then, we cut each video segment into 1 s video clips using a no overlapping sliding window. These clips form the input objects for Stage 2. We then performed the same ROI extraction procedure as for Stage 1 but without video frame downsampling because the frame data are randomly extracted from every second of input, which has an effect similar to downsampling.n = 13) and a relatively large amount of unlabeled data (n = 55). Apparently, the labeled data we have are insufficient to train a deep learning model. To explore the value of the unlabeled data, we adopt a contrastive learning framework similar to SimCLR [n = 2), while the others (n = 2(N-1)) are treated as negative examples. Then the similaritysim of the pair S′ is defined as follows:i, j) is defined asτ denotes a temperature parameter, as in [The dataset used in this work consists of a small amount of labeled data  to map the output feature f to the space where contrastive loss is applied. The contrastive prediction task involves finding the other example j in examples S′(i ≠ j)(n=2N − 1) for example i in each pair. In addition, we impose a restriction that every minibatch input must be a set of continuous frames randomly selected from the video frames of a single subject. This restriction eliminates the possibility of finding existing macrofeatures between different faces during training and helps the model focus on the microfeatures of tics.As shown in k frames (k < 25) to feed to F, which generates visual feature vectors. Every visual feature vector came from one frame of the input video clip and corresponded to one neuron of the LSTM layer. These visual feature vector sequences are then fed to the LSTM network to learn their temporal features and deeper spatial features to accomplish the classification task.In Stage 2, we design a supervised learning framework based on the formerly trained neural network encoder (F). The LSTM network consists of a layer of LSTM with dropout and a fully connected layer with rectified linear unit (ReLU) activation. Specifically, we take a one-second-long preprocessed video clip as the input of this stage and randomly select Lf, which is defined as follows:y denotes a tic label, p is the output prediction of the LSTM network, and α and γ are network hyperparameters.To alleviate the problem of imbalanced categories in our labeled data, we use the focal loss  Lf, whic−4 adjusted by setting the cosine annealing learning rate (LR) and a weight decay of 10-6. Considering the limitation of our dataset, we used the pretrained built-in weights of PyTorch [Chen et al.  showed t PyTorch . The traIn Stage 2, each video clip generates a feature vector of clip-length × 512 through F. Here, clip-length is set as 16, which means that there are 16 frames randomly sampled from each video clip, matching the time-step setting in the LSTM network. The input size of the LSTM is 512 with a drop rate of 0.8; the output size is 128; and the size of the fully connected layer is changed to match the number of classes in each classification task. Considering the limited amounts of labeled data in the study that can easily cause overfitting during training and validation, we adopted the leave-one-subject-out cross-validation scheme in Stage 2, which allows us to evaluate the differences between individual patients. The setting for the overall analysis of a single patient is in line with the real clinical scenario, which is beneficial for the subsequent comprehensive analysis. We assess the effectiveness of our proposed method by calculating the accuracy, precision, recall, F1-score, area under the receiver operating characteristic (ROC) curve (AUC_ROC), area under the precision-recall curve (AUC_PR), and a confusion matrix for each subject evaluation. In the two different classification tasks, we consider different cutoff conditions during the training procedure by observing the following indicators from the validation evaluation: (1) accuracy and (2) the F1-score of the tic category. In addition to the data used for experimental modeling, we also collected individual test video data beyond those used for training verification to verify the universality of the method.The next subsections report the details of the results and provide discussions. Unfortunately, to the best of our knowledge, no public TS dataset for tic detection exists, which makes it difficult to compare the results of our method with other works. Instead, we applied another two kinds of supervised ConvNet architectures, convolutional 3D (C3D) , and temC3D  is a simUsing the classification results for an individual subject, we further examine the misclassified items. Taking Case 1 as an example, as shown in The evaluation results of the binary classification task are shown in To verify the visual representation performance of the unsupervised model in Stage 1, we visualized the final layer features of the neural network encoder using the gradient-weighted class activation mapping (Grad-CAM)  method. t-test was performed on each of the items. The time for evaluation for clinicians was recorded between the start and the end for each video evaluation, and for our model it was calculated as the sum of the time taken for the whole process of our architecture, including preprocessing, model calculation, and postprocessing, among which preprocessing is the most time-consuming process. The subitem clinician review refers to the time taken for the clinician's checking process on the results of our models, which is divided into two categories: <5 min (0−5 min) and <10 min (5−10 min). The results are listed as p values of the two scale-related items are greater than 0.05, which shows no significant difference between the two groups of results. The p value of the time comparison is less than 0.0001, showing that our model can save considerable time on tic detection, especially for videos with frequent tic events, which indicates great potential for clinical application.To verify the validity of the proposed method and the possibility of subsequent integration with scales such as MRVRS , we compFurther evaluation for independent testing was additionally conducted on new data to identify tic events, including 1 new patient video and 4 non-TS patient videos. The binary classification task was adopted for this experiment. In the non-TS patient video testing, as shown in Tourette syndrome is a highly individualized neurological disease whose expression changes over time. In the process of long-term observation, diagnostic evaluation, and management of the patient, the ability to continuously monitor and record tic events is the key to obtaining a patient-specific understanding of the disease. While reviewing and evaluating these monitoring data is a highly time- and cost-intensive process for doctors, the use of computer-assisted detection of tic movements can save time and cost, empower doctors to optimize and adjust medication responses, and help establish a good evaluation and management process for patients. Our work is the first application of a deep learning for video-based assessment of Tourette syndrome.As the above experimental evaluations show, our video-based architecture possesses the ability to detect motor tic events in TS from videos acquired in a natural state. In the classification tasks, we detected two kinds of tics that occur most often in patients. Although the multiclass classification task involves limited motor tic categories in our dataset, it represents a unique result: to the best of our knowledge, no other similar research that has used surveillance video data for automatic tic recognition and classification exists. In the evaluation of subsequent results of the model, we defined some items that frequently appeared on the tic scales applied on these model outcomes and obtained consistent results with those from clinicians based on the MRVRS, which shows the ability to integrate observation-based scales or screening instruments for tics, although our current dataset limited a part of it. If we expand to audio data in the near future, it could be more comprehensive for developing an automatic rating scale of tics. For the binary classification task, it achieved good accuracy on video-clip-based recognition; however, it needs more video data for individual tests and other clinical data to support its outstanding performance in computer-aided diagnosis.From our perspective, this work has application prospects from two main aspects: (a) automatic annotation of a video TS dataset. Because our classification task is based on small video clips, the task model can be used to prelabel the video and can then be checked by a doctor in a subsequent continuous data collection task, thereby reducing the doctor's labeling workload and accelerating the accumulation of labeled data. (b) Home-based health management applications: the extensive use of monitoring cameras makes it possible to extend this work to home-based health monitoring and management since acquiring video at home enhances the retrieval of objective tic expression . In thisThe inadequacy of labeled data is a clear limitation to future work and constitutes a weakness that we alleviate through unsupervised learning methods. We will continue to try to ameliorate this limitation by integrating the few-shot learning method, which has performed well on many tasks with only small amounts of available training data , 43. MorIn this work, we introduce the first application of a deep learning method that combines unsupervised and supervised learning for video-based facial tic motion detection in TS patients. The developed model achieved good classification results on both multiclass and binary classification tasks; it can both detect and classify facial tic behaviors. This study effectively utilized large amounts of unlabeled data, which greatly reduced the labeling workload. A subsequent quantification of tic behavior has potential clinical application value for early identification and auxiliary diagnosis and evaluation of treatment effects. In the future, more video data will be collected and used to evaluate our scheme.


It is believed that stimulating the inspiration of short video consumers might be an effective way to attract and maintain the attention of consumers so that they are willing to respond positively to short video ads. Therefore, in order to explore the source of customer inspiration in short video and its cognitive psychological process, the text and grid data collected from an interview among 25 short video users have been qualitatively analyzed by Kelly Grid Technology in order to construct the formation path model of short video customer inspiration, and find out its source, triggering mechanism, and influencing factors. It is found that the inspiring informational content characteristics include richness, reliability, vividness, and fluency of emotional content characteristics, fun, novelty, and narrative. However, the characteristics of commercial content in short video ads hinder the inspiration of consumers. The study also reveals that an internal mechanism of inspiration stimulation is built on some cognitive processes  generated by informational content, and emotional responses by emotional content . In addition, it is shown that personal involvement enhances the relationship between the inspiring content characteristics and consumer inspiration. As a result, customer inspiration and engagement in short video ads are highly enriched. Findings provide implications for short video platforms and online marketers. With the explosion of information in the era of social media, the limited concentration of consumers is easily distracted or even hardly captured. Despite the vitality and abundance of internet video advertisements, they are also short of effective method to attract the attention of consumers . TherefoWhile short video ads can be an effective marketing tool, it is far from enough to simply rely on the unique or appealing content to improve its marketing performance. On the one hand, consumers who have been constantly suffering from concentration difficulties may swipe the phone quickly to avoid watching short video ads because of their aversion to the commercials . AdditioRecent research on “customer inspiration” may shed light on the way of capturing and maintaining the attention of short video audiences so as to inspire their positive response. Customer inspiration consists of cognitive activation and intention driver, which describes the internal activation state that encourages the attention of the consumer and new ideas for practice . SpecifiIn spite of the significant differences between video advertising and short video advertising in terms of production methods and communication forms, they both essentially reconstruct product attributes, functions, and other business information through audio-visual symbols. In addition, considering that short video research is in the ascendant, it is advisable to refer to the previous studies on video advertising so as to explore the advertising features that can promote communication and consumer purchase. According to the content feature framework of online video advertising shared by consumers , informaIn the classic integrative models of advertising, informational route and emotional route are two main paths to influence consumer attitudes . They caSecondly, emotion-focused content aims at arousing the emotional response of consumers , which iIn addition, distinct from the content produced by non-marketers, commercial nature and persuasive intention are important characteristics of advertising. Customer inspiration is the specific application of the classical social psychology concept “inspiration” in the marketing situation , 2004, iBy combing relevant literature, a large number of empirical analyses have been conducted on the sources of customer inspiration, and their results provide certain implications for research on the triggering mechanism of customer inspiration in short videos. Customer inspiration is not spontaneous but induced by external stimuli of intrinsic value . BöttgerFrom the above literature review, it can be seen that: (1) previous studies on advertising are based on the conceptual framework of informative, emotional, and commercial content, deeply exploring the factors that influence the effectiveness of advertising. Most of the discussions focus on advertising attitude, brand evaluation, viewing behavior, purchase intention, sharing intention, sales, and other dependent variables. However, as mentioned above, customer inspiration that includes cognitive activation and intention-driven components is more helpful to resolve the urgent problems in short video advertising, that is, how to attract and maintain the attention of consumers and prompt them to make a positive response. Unfortunately, there is no research taking customer inspiration as the key concept to explore the effectiveness of short video advertising, which should have been a new perspective in the field. (2) A number of advertising features related to information, emotion, and commerce have been identified, and marketing drivers with heuristic traits  have also been extensively validated. However, the short video, as a new media, is different from other social media applications in terms of content generation, display, browsing and transmission . Moreover, customer inspiration largely depends on the situation that generates it. The existing characteristics of inspiration may not be applicable to short video advertising. It is therefore necessary to use the current content framework to explore new factors that influence the generation of inspiration of short video customers and its triggering mechanism.This study aims to explore the triggering mechanism of customer inspiration in short videos. In view of the lack of mature theories and studies on this issue, the qualitative research method is given priority. Specifically, the Repertory Grid Technique (RGT) has been adopted in research interviews and data collection. RGT originates from the personal construct theory in cognitive psychology. The constructs accumulated in life are used to explain and predict the events around . Kelly . This isAlthough customer inspiration is not essentially a mystic experience , it is sMage = 22.4). The interview was conducted face-to-face, with each interview lasting from 33 to 97 min (M = 56)  . Ultimat1 prepared by the researchers one by one, and to select from them three ads that can stimulate inspiration and three that cannot. The selected six ads are written on a separate card in digital form. Secondly, according to the highly respected triads method , which confirms the above conclusions. In the square example of In the formal interview, researchers first explained the meaning of customer inspiration to the respondents to ensure that they can understand the concept properly. The respondents were informed of the two parts in the experience of customer inspiration, namely, to obtain new ideas or possibilities from the external marketing stimuli, thus experiencing a ‘flashing’ moment of being enlightened as shown in the words like “Aha!,” “Eureka!,” etc., and to generate motivation to implement new ideas, such as the strong desire to buy or use products. The specific interview steps are as follows. First of all, each respondent needs to watch the 16 highly inspiring short video advertisements (elements)s method , three cs method . It is ws method . In parts method . The proThe recorded audio interview process was transcribed into a written text of more than 60,000 words before data analysis. The analysis of quantitative and qualitative data of transcribed text precisely follows the method adopted by A small number of constructs in the interview are same in meaning but slightly different in expression. After carefully examining all the text content and grids, two researchers in charge of data collection identified and standardized the duplicate constructs. For example, 15 interviewees admitted that they are inspired when the short video ads provided a sensory experience of audio-visual conformity. But they used ‘audio-visual conformity,’ ‘audio-visual coordination,’ ‘audio-visual match,’ ‘audio-visual fit,’ and other expressions in the positive construct pole. The inconsistency of this kind was also found in the negative construct pole. To the end, ‘audio-visual conformity’ was determined as the standard construct name. Through such a process of standardization, 279 initial constructs have been simplified to 50. Furthermore, in order to ensure the significance of the analyzed constructs, the constructs that had been mentioned by at least three interviewees (≥12%) were finally retained, with a total of 39 constructs.Based on the inherent meaning of and interaction between constructs, 39 standardized constructs were categorized in accordance with their themes. This categorization strictly followed the four steps recommended by the prior research , namely,As shown in According to the model, customer inspiration is significantly affected by the inspiring informational content characteristics, emotional content characteristics, and commercial content characteristics in which the characteristics of informational content mainly activate the cognition-dominated processing mechanism, that of emotional content which arouse the emotion-dominated processing mechanism, and of commercial content which exert a direct impact on customer inspiration. Besides, the possibility of triggering inspiration in short videos is influenced by customer personality. This part of the article is to illustrate the source, triggering mechanism and influencing factors of customer inspiration in short videos, and draws the corresponding research propositions.Many scenes in the short videos about laser keyboard and engraving machine have been switched, so I think they have a lot of uses. The scenes of the other two videos are relatively unchanged, nothing new” (Respondent 11). Secondly, the reliability of short video ads refers to the credibility of the informational content, with an intention of helping consumers better understand the product features. This raises their initiatives to accept the new ideas guided by marketing. Reliability depends on the authenticity and professionality of content. As one respondent puts it, “The short video of smart suitcase reflects the feelings of both the users and the onlookers. This can be called objectivity. But in the video about cookies and milk, only one person and his experience are recorded. That is too subjective. If a short video fails to display every aspect of a product, I will not pay much attention to it” (Respondent 06). On the other hand, based on dual coding theory, the interpretation of an individual of informational content varies significantly from linguistic to non-linguistic system . Secondly, novel short video ads have prominent emotional driving effect because of their distinctive content or the way it is presented. It is found in the study that novelty brings about surprise and curiosity that provide consumers strong desires to explore new things. In addition, narrativity depicts an intense emotional experience created by the story in short videos, which also encourages an incentive to the pursuit of consumption-related goals. Narrativity is composed of three elements, namely, plot, surprise, and story, with its intensity increased by the application of these elements. In fact, respondents can accurately identify the organization of content that drives emotional experience: “The videos of porphyra rice and shadow lamp adopted a way of story telling. They were shot in a very dramatic way. I just couldn’t take my eyes away” (Respondent 18).Different from the informational content characteristic that convince consumers to accept new ideas and possibilities promoted in marketing in the way of persuasion, communication, and knowledge dissemination, the emotional content characteristic of short video ads may generate the intrinsic motivation of consumers to pursue consumption-related goals by stimulating their positive emotional response , which iIn accordance with the findings in the previous research about the novelty in customer inspiration , this stP2: Fun, novelty, and narrativity of short video ads promote the generation of customer inspiration.As to the yogurt candy videos, the sales pitch is too purposeful. I just want to skip it. The other two videos are not trying to sell anything, they just tell you what it is” (Respondent 08).Studies on video advertising have shown that high level commercial content negatively affect sharing behavior . A similAs previous studies have shown, extrinsic incentives (such as low price and discount) in advertisements can stimulate the avoidance motivation of consumers. But approach motivation will arouse the inspiration of consumers . It is aP3: Commercial intention in short video ads hinders customer inspiration.During the interview, the respondents were often found to spontaneously elaborate their preference to a construct pole, which, in many cases, helps to establish a very clear causal path . In the Wow! It can be used like this!” (Respondent 05). Social psychology shares agreement in that inspiration is closely related to cognition, and the key to its triggering lies in that evocative cognitive event that can promote the understanding of values by people . A recent study also confirmed that the key to inspiring consumers with brand video advertising is to allow them to identify important values through alternative experiences . Based on this, the following proposition is obtained:Because the informational content focuses on rational description, it mainly activates the cognitive dominated processing mechanism , i.e., ty people . In addieriences . SecondlP4: Presence, processing fluency, perceived innovation, and perceived convenience establish an important path to connect the informational content characteristic to customer inspiration.I’m particularly curious about how these amazing and convenient functions of the smart suitcase can be achieved. I’m also curious about how the stickies suck in the dirt. They are quite useful. These two videos make me curious, and I will make it out, see what I can find” (Respondent 12). In fact, the analysis of grid data suggests that arousing an emotional experience of curiosity is the determinant of identifying potentially high and low inspiring advertisements. Secondly, novel short video ads also create surprise. Therefore, consumers are encouraged to eliminate inconsistencies in their cognitive schema and to try some new things. As one of the respondents mentioned, “I was amazed at the technological change after watching these two short video ads. That’s quite different from another one. I’d never believed it could be used in this way. And this astonishment aroused my strong interest” (Respondent 19). This statement is also consistent with the view of The content in the first two videos is progressing step by step. I can see the process of production, and imagine what it will be. I feel especially happy when I see the final product. I want to do it myself” (Respondent 13). Accordingly, the following proposition can be obtained:Since emotional content focuses on perceptual description, it mainly arouses the emotion-dominated processing mechanism , i.e., tP5: Curiosity, surprise, and pleasure form an important path to connect the emotional content characteristic to customer inspiration.The first two videos are in line with my preferences and interests. I really like the art with lighting effect. I like porphyra rice and I once made it myself. Such content will naturally fill my imagination and make me feel better” (Respondent 20). Therefore, the following proposition is obtained.Admittedly, inspiring informational content and emotional content stimulate customer inspiration in most cases, there still exist some factors that can affect the frequency and intensity of customer inspiration in short videos , 2004. RP6: Personal involvement enhances the relationship between content characteristic and customer inspiration.With a focus on the source of customer inspiration of short videos and its cognitive psychological process, 25 short video users were interviewed by RGT qualitative research method. Through the analysis of text and grid data, this article constructs the formation path model of short video customer inspiration, and systematically discusses the source, triggering mechanism and influencing factors of short video customer inspiration. The main conclusions are as follows: the inspiring informational content characteristics in short video ads include richness, reliability, vividness, and fluency, while the emotional content characteristics include fun, novelty, and narrativity. However, the commercial content characteristics of short video ads prevent customers from being inspired. Secondly, cognitive processing such as presence, processing fluency, perceived innovation and perceived convenience caused by informational content characteristics and emotional responses such as curiosity, surprise, and pleasure aroused by emotional content characteristics are the internal mechanism that stimulates customer inspiration in short videos. In addition, personal involvement enhances the relationship between inspiring content characteristic and customer inspiration.First of all, this article creatively takes customer inspiration as the key construct to explore the effectiveness of short video ads, and provides a new theoretical perspective and methodological instruction for researches and practice on advertising. Specifically, with a different perspective from the previous researches that focused on the key variables such as viewing time , sharingSecondly, RGT is applied in this article to sort out the content characteristics that influence the generation of customer inspiration in short videos, the cognitive psychological process triggered by customer inspiration, and the key influencing factors. The findings enrich the existing advertising content feature framework and literature on customer inspiration. In specific, the content feature framework of online video advertising constructed by The research findings may help to resolve some practical problems on how to attract and maintain the attention of consumers and prompt them to make positive response. For online marketers, it is necessary in the design of short videos to have an overall consideration of the inspiring  content characteristics, increasing richness and reliability of informational content and presenting the information vividly and smoothly. Such practice is conducive to stimulating the cognitive process of customer inspiration. Similarly, emotional content that can arouse consumers positive emotional reactions  should also be designed, like adding the funny and novel things to short video ads or displaying presenting the experience of product in a narrative way. In addition, marketers should try to reduce the commercial intention of short-video ads such as sales labels with persuasive bias, thus attracting the attention of consumers to the theme of advertising. Therefore, by increasing the probability of inspiration, consumers can be encouraged to actively participate in short video ads, such as browsing, sharing, purchasing, and other engagement behaviors. The short video platforms can increase the exposure rate of high inspiring short video ads by adjusting the content distribution algorithm so as to attract more consumers for businesses. Furthermore, user portrait algorithm can be improved by collecting data related to user involvement  to increase the frequency and intensity of inspiration, which will greatly improve the rate of purchase conversion of short video ads.As an exploratory study, there inevitably exist insufficiencies that need to be further investigated. Firstly, although the selected samples are representative and the number of samples also meets the requirements of theoretical saturation, the small sample size is not large enough to provide us with sufficient evidence for more convincing conclusions. Future studies should employ a large-scale questionnaire survey to test the reliability of the constructed conceptual model. Second, despite the preciseness of strategies in the selection of short video ads, subjective involvement in the procedure may reduce the validity to some extent. Therefore, attempts can be made to include emotion or sensation analysis of comment text in short video ads in order to sort out the most effective inspiring stimuli for experiment. In addition, the proposed content characteristics  that affect the customer inspiration can be well manipulated in the experiment. In future studies, the causal relations in the six research propositions and the impact of each factor on customer inspiration experience should be analyzed and verified by experiments. Finally, while customer inspiration may well explain how short video ads attract attention and motivate positive response, real behavioral indicators are more instructive for marketers and should be applied to the construction of future research framework.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by School of Economics and Management, Northwest University. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.PG: conceptualization, methodology, writing – review and editing, supervision, and funding acquisition. HJ: investigation, resources, and writing – original draft. YX: formal analysis and project administration. YC: data curation and visualization. All authors: contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


We investigated the anthropometric characteristics associated with specific handball skills in competition. The body anthropometric profiles differ significantly among the playing positions in handball due to the specific tasks. The aim of this study is to identify the anthropometric patterns for each playing position by collecting data from elite male handball players. To determine the anthropometric profile of the elite handball players for each playing position, we used descriptive statistics for every indicator in order to identify the optimal patterns for elite handball players from the top-four ranked teams at the most important competitions over a period of 18 years (2004–2021). Over time, the anthropometric indices evolved: the average height increased (from 190 to 192.6 cm) but less than weight increased (from 90.5 to 95.28 kg), and these affected the body mass index (increase from 25.2 to 25.67). The novelty of our study is that we identified an anthropometric pattern for each playing position and for all teams in elite male handball. Our study also covered a period of 18 years to give our results more accuracy and reliability. Currently, along with good sport preparation for elite athletes, the specific anthropometry indices are essential in order to achieve performance in top competitions in collective sports where others are also important: maturity status , capacitIn elite sport, the anthropometric indices have a major impact on performance ,20,21,22Handball has a complex character due to the acyclic movements and situations that appear asking players performing tasks according to the playing position both in attack and in defense. The modern handball game requires players to perform a high number of short, high-intensity specific actions. Based on these considerations, we can state that the features of anthropometric and motor particularities have a high degree of individualization according to the playing position, and it is interesting to determine how personal predispositions can compensate or substitute particular requirements of the playing position.Somatic and skills indicators of the players can be essential in achieving certain tasks within the game, as in other game situations, they can be a barrier having a limited effect ,32. The Body anthropometric profiles differ significantly among the playing positions in handball due to the specific tasks. From the anthropometric point of view, the wing players were found to be lighter (79.7–81.7 kg) and shorter (177.1–178.3 cm) than backcourt players , goalkeepers  and pivots ; pivots were heavier than centers (83.6–90.5 kg); backcourt players and pivots had higher muscular mass than wings; backcourt players had higher hand-grip values; and the line players (pivots) were the heaviest players.The majority of elite handball players are part of the mesomorph and endomorph somatotypes; however, according to the playing positions, the backcourt players are mesomorph, wings and pivots showed an endomorph–mesomorph somatotype, and goalkeepers were in the ecto-endomorph somatotype zone ,34,35. TFrom 1960 and 1970, there was information concerning the anthropometric characteristics of the elite handball players for each playing position, and, at least for weight, there are some differences compared to the current requirements . In the A study concerning the anthropometric indices at senior handball teams participating in the competition E.H.F. Champions League, Final Four 2012 showed average values higher than in previous periods ; however, there were only a small number of handball players (62) compared to O.G., W.C. and E.C., and it is important to mention that all of them are elite players of the best four teams in Europe and possibly of the world . AnotherOver time, there have been studies concerning physical characteristics of the male handball players with different numbers of participants and performance levels  .In the studies with a small number of participants, the anthropometric data were collected directly by measuring handball players ,46,47,48Based on the somatic requirements on high performance selection in handball, we can say that, in terms of height, only 25% of the population would meet the standard. The weight and the essential skills  can compensate for a lower height . The aimThis is a cross-sectional study where we use a descriptive analysis of the anthropometric indices of players at handball top competitions . The information concerning the anthropometric characteristics (weight and height) was collected from the EHF and IHF websites that present all information, including the team roster . The data were obtained through an informative portal  without the necessary knowledge about the methodology of its collection in order to assess its reliability and validity ,62,63,64Our study collected data from 974 players participating at O.G., W.C. and E.C., as components of the teams ranked in the first four places at each competition. Each team had between 16 and 18 players listed for competition.Inclusion criteria: male handball players from top-four ranked teams at O.G., W.C. and E.C. in the period 2004–2021. Exclusion criteria: female or male handball players from teams ranked out of the top four at O.G., W.C. and E.C. Due to the fact that this covers a period of 18 years, the data for the same player were used as long as he participated in these top handball competitions.Descriptive statistics were applied in order to identify the anthropometric patterns  for each playing position . The study collected information for almost 20 years (2004–2021). At O.G., there were 12 teams involved in the final stage; at W.C., 24 teams/32 teams (since 2021); and at E.C., the number rose from 16 to 24 teams (since 2020). The data were collected only from the players of the teams placed in the first four places at each analyzed competition.To determine the anthropometric profile of the elite handball players for each playing position, we used descriptive statistics by applying the average, standard deviation, minimum value and maximum value for every indicator in order to identify the optimal patterns for elite handball players. We applied linear regression to find significant relationship between the variables used in our study using IBM SPSS Statistics 26. The coefficients for regression equation and tests of significance were the most important data obtained by applying this statistical method.Starting with O.G. 2004, data were collected for anthropometric characteristics of the male handball players who participated at O.G., W.C. and E.C. in order to identify the specific patterns for each playing position. We calculated the means for each parameter, standard deviation, minimum value and maximum value for each playing position and for all players. All collected data are presented in All the collected data allowed us to find useful information concerning anthropometric characteristics of the elite handball players for each playing position. The synthetic information for all analyzed competitions is presented in p < 0.05. 6 for p < 0.01, three for p < 0.001, and four for p < 0.0001. Statistical significance  and also the lightest players . The BMI average was 24.625, meaning they were normo-ponderal with a lower limit of 23.3 and an upper limit of 25.9. For all wing indicators, there were obtained statistical significance for  < 0.001  [14,35,4p < 0.01 (height) and for p < 0.001 (weight and BMI)  and backcourts  were the tallest and also the heaviest players, pivots—105.096 kg with accepted limits between 98 and 113 kg and backcourts—98.553 kg with optimal values between 92 and 105 kg. The average BMI for pivots was 27.207 and 25.588 for backcourts. For pivots, there was significance for and BMI)  [14,35,4Goalkeepers were close in value to pivots and backcourts . At linear regression, we obtained statistical significance only for the BMI of goalkeepers  14,35,4,65,66.p < 0.0001) (Backcourts were close in height to pivots (1.962 m), but lighter (98.553 kg) and the limits for BMI are between 24.2 and 27. The highest values of coefficients at linear regression were achieved at backcourts indicators ( 0.0001)  [14,35,4p < 0.01 (weight and BMI) and p < 0.001 (height) ; the weight average was 92.697 kg (minimum—86 kg and maximum—99 kg); and the BMI average values was 25.609 (accepted range between 24.1 and 27.1). The level of significance for centerback indicators were for (height)  [14,35,4p < 0.001 (height) and p < 0.0001 (weight and BMI)   [14,47,4We consider the identified pattern in our study for each playing position valid as, in 16 out of 18 situations, we obtained statistical significance at linear regression, and the data were collected for a period of almost 20 years from 974 top male handball players .Over time, the anthropometric pattern changes for each playing position compared to those in 1970 and 1980. The values for height and weight increased with an average value of 5%. The most important evolution trend was for pivots where the height increased by 7% and the weight by 20% ,39.Comparing the results to recent studies concerning the anthropometric pattern for top male handball players, there are no differences ,40,67,68An interesting fact is that the pivots were the tallest (197 cm) and heaviest handball players (105 kg), as the backcourts (196 cm) are usually associated as the highest handball players. To identify the anthropometric pattern in our study, only players from the top four were included for each analyzed competition from the best male handball teams for period 2004–2021.Every year, the I.H.F. awards the world’s best players; five goalkeepers, four centerbacks and two backcourts were nominated for the analyzed period. In that period of time, Nicola Karabatic and Mikkel Hansen were nominated three times. The world’s best players were in the limits of the anthropometric pattern identified in our study. The exception being the goalkeeper Arpad Sterbik, who exceeded the upper limits. This aspect confirms the validity of the anthropometric pattern determined by our study .The anthropometric pattern was found to evolve over time: the average height increased (1.4%) but less than the average weight (4.5%), thereby, influencing the average body mass index (2.7%). More weight in the case of elite handball players typically means more muscular mass required by the modern handball player in order to be effective in game actions during the competitions.Anthropometric characteristics, including the body composition and the somatotype of the elite handball players, are specific to the playing position in order to allow them to efficiently act in competitions. Among these indicators, the specific preparation of handball players is essential to achieve competition goals and to be efficient in specific actions during the game.The limitations of the study include access to data concerning only height and weight and indirect data collection from the official website of the International Handball Federation and European Federation. For the future, it will be important to collect data for other variables, such as the body composition, skinfold thickness and body circumference. Among other factors, the anthropometric pattern is essential when a coach wants to select a player for his team, and it is optimal to choose a player that meets these requirements concerning anthropometric patterns.The novelty of our study is that we identified an anthropometric pattern for each playing position and for all teams in elite male handball, and our study covered a period of 18 years to give our results more accuracy and reliability. These identified patterns will be subject to change over time, and further studies are necessary in order to keep these anthropometric models updated.