Wearable Sensor-Based Real-Time Gait Detection: A Systematic Review

Sensors, 2021 · DOI: 10.3390/s21082727 · Published: April 13, 2021

Assistive Technology Biomedical Biomechanics

Simple Explanation

This review looks at using wearable sensors for real-time gait analysis, which is important for developing gait rehabilitation techniques and assistive devices. It identifies the most commonly used sensors, their placements, and methods for detecting gait events. The review found that inertial measurement units (IMUs) are the most widely used wearable sensors, with the shank and foot being the preferred placements. Heel strike and toe off are the most sought-after gait events. The review also highlights that a combination of IMU and rule-based methods is an optimal solution for clinical applications of gait detection algorithms.

Study Duration

Not specified

Participants

Not specified

Evidence Level

Level 1: Systematic Review

Key Findings

1
Heel strike and toe off are the most widely identified gait events, irrespective of the type of sensor used.
2
Inertial measurement units (IMUs) are the most widely used sensors, with 77% of studies using them alone or in combination with insole pressure sensors (IPSs).
3
Rule-based methods are the most widely used gait detection technique, employed by 63 out of the 99 studies, likely due to their simplicity and intuitiveness.

Research Summary

This article presents a systematic review of wearable sensors and techniques used in real-time gait analysis, and their application to pathological gait. We found that heel strike and toe off are the most sought-after gait events. Inertial measurement units (IMU) are the most widely used wearable sensors and the shank and foot are the preferred placements. Clinical applications of gait detection algorithms were considered, and we recommend a combination of IMU and rule-based methods as an optimal solution.

Practical Implications

Rehabilitation Techniques

Real-time gait analysis is key to the development of effective gait rehabilitation techniques.

Assistive Device Control

Real-time gait analysis enables the control of assistive devices such as neuroprostheses.

Clinical Application

Combining IMU and rule-based methods provides an optimal solution for clinical gait detection.

Study Limitations

1
Heterogeneity of evaluation criteria prevented quantitative performance comparison of all methods.
2
Less than one third of studies were validated on pathological gait data.
3
The performance of gait detection methods could not be compared quantitatively due to the heterogeneity of the metrics used across the algorithm types.

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