{'fraction_non_alphanumeric': 0.012552301255230125, 'fraction_numerical': 0.0, 'mean_word_length': 5.5227272727272725, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Computer vision technologies for monitoring system in tele-physiotherapy

Physiotherapay exercise is a vital medical treatment process as it helps bringing a normal life back to patients. However due to the requirements of time spent and interactions with medical specialists such as doctors, therapists, and nurses, patients have to deal with some difficulties such as time and cost of travelling, waiting for availability of specialists and ineffective personal exercises. These difficulties could cause worse on those patients living in the areas distant from medical centres or lacking of medical staffs and experts. Therefore the concept of tele-physiotherapy was created to improve the quality of physiotherapy services. The objective of tele-physiotherapy is to allow patients and medical experts carrying on their sessions through telecommunication networks as if they are in the same place. Computer vision technologies, then, can be useful and helpful in monitoring process of system because the quality assessments of physiotherapy exercise are mainly based on vision. This article is discussing the feasibility of applying computer vision technolgies in tele-physiotherapy while showing an example of using computer vision in fall detection. The study shows that computer vision has some potentials in enhancing and improving the telephysiotherapy system but the study of some considerations is needed before implementing.