Comparison of walking data between elderly and healthy persons using Self-Organizing Maps

• Published in: Proceedings of the Annual Conference of Biomedical Fuzzy Systems Association Vol. 35; p. J-2
• Main Authors: Gonda, Eikou, Ohba, Haruka, MIYATA, Hitoshi
• Format: Journal Article
• Language: Japanese
• Published: Biomedical Fuzzy Systems Association 2022; バイオメディカル・ファジィ・システム学会
• Subjects: Elderly people; Fall prevention; Load data; Self-organizing maps; Walking
• ISSN: 1345-1510; 2424-2586
• DOI: 10.24466/pacbfsa.35.0_J-2

In recent years, Japan's population has been aging, and the "increase in the number of people requiring nursing care" has been cited as a social problem due to the aging of the society. Injuries such as fractures due to falls account for approximately 12.5% of all injuries, making it the fourth most common cause of care needs. Falls are a major cause of injury for the elderly, and even in the absence of trauma, fear of falling may cause gait disturbance called post-fall syndrome. Therefore, we thought that falls could be prevented by studying the causes and countermeasures of falls among the elderly. In this research, we used a plate-type distributed pressure system to obtain load data and basic data from elderly and healthy subjects, and analyzed and compared the data usinga Self-Organizing Maps (SOM), which is used to group data with similar characteristics. In the previous year's research, we compared the data for each foot, but this year we analyzed how the load changes during the flow of walking, such as the first and second steps. The SOM created as a result of the analysis showed that the load data and basic data were divided into four groups, and by examining these groups, we were able to understand where the load data and basic data were located for each characteristic, and we also found that gait was improved before and after exercise.