A practical gait feedback method based on wearable inertial sensors for a drop foot assistance device

Lin Meng, Uriel Martinez-Hernandez, Craig Childs, Abbas A. Dehghani-Sanij, Adrjan Buis

Research output: Contribution to journalArticle

Abstract

To maximise the efficiency of gait interventions, gait phase and joint kinematics are important for closing the system loop of adaptive robotic control. However, few studies have applied an inertial sensor system including both gait phase detection and joint kinematic measurement. Many algorithms for joint measurement require careful alignment of the inertial measurement unit (IMU) to the body segment. In this paper, we propose a practical gait feedback method, which provides sufficient feedback without requiring precise alignment of the IMUs. The method incorporates a two-layer model to realise simultaneous gait stance and swing phase detection and ankle joint angle measurement. Recognition of gait phases is performed by a high-level probabilistic method using angular rate from the sensor attached to the shank while the ankle angle is calculated using a data fusion algorithm based on the complementary filter and sensor-to-segment calibration. The online performance of the algorithm was experimentally validated when 10 able-bodied participants walked on the treadmill with three different speeds. The outputs were compared to the ones measured by an optical motion analysis system. The results showed that the IMU-based algorithm achieved a good accuracy of the gait phase recognition (above 95%) with a short delay response below 20 ms and accurate angle measurements with root mean square errors below 3.5º compared to the optical reference. It demonstrates that our method can be used to provide gait feedback for the correction of drop foot.
LanguageEnglish
Number of pages9
JournalIEEE Sensors Journal
Early online date2 Sep 2019
DOIs
Publication statusE-pub ahead of print - 2 Sep 2019

Fingerprint

gait
Feedback
Units of measurement
sensors
Sensors
Angle measurement
Kinematics
Exercise equipment
Plant shutdowns
Data fusion
Mean square error
Robotics
treadmills
kinematics
alignment
joints (junctions)
Calibration
root-mean-square errors
multisensor fusion
systems analysis

Keywords

  • inertial measurement units
  • gait analysis
  • gyroscopes and accelerometers
  • gait phase recognition
  • ankle angle measurement
  • hierarchical structure
  • sensor data fusion

Cite this

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title = "A practical gait feedback method based on wearable inertial sensors for a drop foot assistance device",
abstract = "To maximise the efficiency of gait interventions, gait phase and joint kinematics are important for closing the system loop of adaptive robotic control. However, few studies have applied an inertial sensor system including both gait phase detection and joint kinematic measurement. Many algorithms for joint measurement require careful alignment of the inertial measurement unit (IMU) to the body segment. In this paper, we propose a practical gait feedback method, which provides sufficient feedback without requiring precise alignment of the IMUs. The method incorporates a two-layer model to realise simultaneous gait stance and swing phase detection and ankle joint angle measurement. Recognition of gait phases is performed by a high-level probabilistic method using angular rate from the sensor attached to the shank while the ankle angle is calculated using a data fusion algorithm based on the complementary filter and sensor-to-segment calibration. The online performance of the algorithm was experimentally validated when 10 able-bodied participants walked on the treadmill with three different speeds. The outputs were compared to the ones measured by an optical motion analysis system. The results showed that the IMU-based algorithm achieved a good accuracy of the gait phase recognition (above 95{\%}) with a short delay response below 20 ms and accurate angle measurements with root mean square errors below 3.5º compared to the optical reference. It demonstrates that our method can be used to provide gait feedback for the correction of drop foot.",
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A practical gait feedback method based on wearable inertial sensors for a drop foot assistance device. / Meng, Lin; Martinez-Hernandez, Uriel ; Childs, Craig; Dehghani-Sanij, Abbas A. ; Buis, Adrjan.

In: IEEE Sensors Journal, 02.09.2019.

Research output: Contribution to journalArticle

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