The characteristics of ankle joint motions in the elderly that arise from a wide range of activities of daily living (ADLs) have not been adequately assessed using a quantitative and objective pattern recognition approach. The current study aims to analyze the characteristics of ankle joint motions for 12 different ADLs in the elderly through the pattern recognition approach; this study also aims to identify whether this analysis technique is effective, quantitative and objective in understanding the characteristics of ankle joint motions. Fifty elderly participants performed 12 ADLs that were selected based on Katz’s ADL indicators. Inertial measurement units were used to measure the ankle joint motions, and their patterns and similarities were analyzed using the pattern recognition approach. The results identified the inherent ankle joint motion features for each ADL. The similarities of the patterns of ADLs related to walking were very low (p < 0.25) for the ankle joint motions even though the range of motion and pattern shapes were similar to one another. The similarities of the patterns of ADLs related to sitting/rising were particularly high (p > 0.9) for dorsi/plantar flexion and low (p < 0.5) for abduction/adduction. The similarities of the patterns of ADLs related to lying/rising were high, particularly for dorsi/plantar flexion and inversion/eversion. The results suggest that applying a pattern recognition approach with a conventional kinematic analysis may be effective, quantitative, and objective in understanding the kinematic characteristics of ankle joints.
|Number of pages||14|
|Journal||International Journal of Precision Engineering and Manufacturing|
|Publication status||Published - 2020 Jun 1|
Bibliographical noteFunding Information:
This research was supported by a Grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare (Grant No. HI15C2149), Republic of Korea.
© 2020, Korean Society for Precision Engineering.
All Science Journal Classification (ASJC) codes
- Mechanical Engineering
- Industrial and Manufacturing Engineering
- Electrical and Electronic Engineering