Wearable Inertial Sensors for Human Motion Analysis: A Review

This paper reviews the research literature on human motion analysis using inertial sensors with the aim to find out: which configuration of sensors have been used to measure human motion; which algorithms have been implemented to estimate position and orientation of segments and joints of human body; how the performance of the proposed systems has been evaluated; and what is the target population with which the proposed systems have been assessed. These questions were used to revise the current state-of-the-art and suggest future directions in the development of systems to estimate human motion. A search of literature was conducted on eight Internet databases and includes medical literature: PubMed and ScienceDirect; technical literature: IEEE Xplore and ACM Digital Library; and all-science literature: Scopus, Web of Science, Taylor and Francis Online, and Wiley Online Library. A total of 880 studies were reviewed based on the criteria for inclusion/exclusion. After the screening and full review stages, 37 papers were selected for the review analysis. According to the review analysis, most studies focus on calculating the orientation or position of certain joints of the human body, such as elbow or knee. There are only three works that estimate position or orientation of both, upper and lower limbs simultaneously. Regarding the configuration of the experiments, the mean age of the test subjects is 26.2 years (± 3.7), indicating a clear trend to test the systems and methods using mainly young people. Other population groups, such as people with mobility problems, have not been considered in tests so far. Human motion analysis is relevant for obtaining a quantitative assessment of motion parameters of people. This assessment is crucial for, among others, healthcare applications, monitoring of neuromuscular impairments, and activity recognition. There is a growing interest for developing technologies and methods for enabling human motion analysis, ranging from specialized in situ systems to low-cost wearable systems.