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Updated: Jun 19, 2025

Home-Based Monitor for Gait and Activity Analysis
Published on: August 8, 2019
Recent Advances in Self-Powered Wearable Flexible Sensors for Human Gaits Analysis
Xiaohe Hu1, Zhiqiang Ma2, Fuqun Zhao1
1School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China.
This review covers self-powered wearable flexible sensors for detecting human movement in exoskeleton devices. It discusses sensor design, algorithms, and future implementation challenges for enhanced human-machine interaction.
Area of Science:
- Materials Science
- Robotics
- Biomedical Engineering
Background:
- Flexible electronics are advancing rapidly, creating a need for effective human motion detection in exoskeleton systems.
- Wearable sensors are crucial for gathering real-time human movement data to control auxiliary equipment.
- Current research focuses on integrating advanced sensors into assistive technologies.
Purpose of the Study:
- To review recent advancements in flexible electronics for human motion detection.
- To explore self-powered wearable flexible sensors for exoskeleton applications.
- To discuss algorithms and future perspectives in this field.
Main Methods:
- Comprehensive literature review of self-powered wearable flexible sensors.
- Analysis of algorithms for human movement feedback.
- Discussion of fabrication methods and sensor effectiveness.
- Examination of challenges and opportunities in exoskeleton technology.
Main Results:
- Overview of various self-powered wearable flexible sensor designs and fabrication techniques.
- Presentation and evaluation of algorithms for processing human movement data.
- Identification of key performance metrics for sensor accuracy and reliability.
- Summary of current limitations and potential breakthroughs.
Conclusions:
- Self-powered wearable flexible sensors show great promise for exoskeleton control.
- Further research is needed to overcome challenges in sensor durability, power management, and algorithm integration.
- Successful implementation requires interdisciplinary collaboration between materials science, robotics, and human-computer interaction.
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