# A Review on Computer Vision Technology for Physical Exercise Monitoring
## 2 Data Sources  
The original research studies were sourced from the IEEE Xplore, ScienceDirect, Web of Science, Spring link, PubMed, Psych info, ACM digital library, and Human and kinetics journals. The search criteria were: (\"Physical exercise\" OR \"Physical activity\" OR Exercise OR \"Physiological features\" OR Fitness) AND (Monitoring OR Monitor OR measurement) AND (non-invasive OR Contactless OR non-contact OR contact free). The publication years of the research articles were selected from 2000 to 2022. Original research articles published in journals, conference proceedings, book chapters, and review papers were selected for the review. Table 1 presents the Inclusion and Exclusion criteria for the article selection.  
\begin{table}
\begin{tabular}{l l l} \hline \hline \multicolumn{1}{c}{**Inclusion Criteria**} & \multicolumn{1}{c}{**Exclusion Criteria**} \\ \hline \(\bullet\) & Published in 2000 and later & \(\bullet\) & Published other than English articles \\ \(\bullet\) & Included physical exercise monitoring using supervised & \(\bullet\) & Published before 2000 \\  & and non-invasive methods. & \(\bullet\) & Published as editorial, abstract only, newsletters, poster, \\ \(\bullet\) & Papers that evaluated the validity of physical activity & \(\bullet\) & letter to editor, commentaries, interviews. \\ \(\bullet\) & classification models/algorithms or papers that outlined algorithm development. & \(\bullet\) & Existed as multiple publications from same authors of same study. \\ \(\bullet\) & Included all types of datasets (facial or other images, subject may be any age) & \(\bullet\) & Publications related to physical exercise monitoring with contact sensor techniques. \\ \(\bullet\) & Include all types of image processing and data analysis techniques. & \(\bullet\) & Publications related only physiological parameter measurements (Heart rate, Respiratory rate, etc.) in resting or other conditions. \\ \hline \hline \end{tabular}
\end{table}
Table 1: Inclusion and Exclusion Criteria for the article selection.  
The methods of the systematic review have been developed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The completed PRISMA-P [9] checklist is available as a supplementary file to this protocol. The article collection and selection were performed in three different stages. The article collection flow diagram using the PRISMA flow diagram is shown in Figure 1.  
Stage 1: The first stage is about the selection of articles according to the title. In this stage, the duplicate articles from various databases were removed and irrelevant articles only according to the title were removed from the list.  
Stage 2: In this stage, the abstract of the articles is reviewed. The methodology and results were also reviewed in this stage. The articles that have irrelevant methodology and poor results were removed and the articles that have similar methodologies were also filtered out.  
Stage 3: In this stage, the articles selected from stage two were fully read and the results were analyzed thoroughly. The final extraction output will be compared with others.  
_Taxonomy_  
It has three levels of taxonomy; Analysis Parameters, Target Group, and Intelligent Output (See Figure 2). Level 1 is about the data collection or raw input data, which includes how and what type of data are collected to monitor the physical exercises. The second level includes input and output information focused for the target group. In particular, how the data collected in Level 1 is processed to obtain meaningful information. The  
Figure 1: Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram for the data article collection and screening.  
third level includes some intelligent processing to obtain meaningful full information from the data collected from the subject. Machine learning and deep learning techniques are implemented at this level.