Development and Evaluation of a Kinect-Based Motion Recognition System based on Kalman Filter for Upper-Limb Assistive Device

Liao, Yun-Ting; 杨浩,; Lee, Hee-Hyol; Tanaka, Eiichiro

doi:10.23919/sice.2019.8859744

Cited by 6 publications

(1 citation statement)

References 9 publications

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“…Liao et al proposed a motion intention recognition system based on the Kinect V2 sensor. It can successfully provide an adequate assistance with a lesser time delay compared with the system without Kalman filter [27].…”

Section: Introductionmentioning

confidence: 99%

An LSTM-Based Prediction Method for Lower Limb Intention Perception by Integrative Analysis of Kinect Visual Signal

Guo

Shao

et al. 2020

Journal of Healthcare Engineering

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Recently, computer vision and deep learning technology has been applied in various gait rehabilitation researches. Considering the long short-term memory (LSTM) network has been proved an excellent performance in learn sequence feature representations, we proposed a lower limb joint trajectory prediction method based on LSTM for conducting active rehabilitation on a rehabilitation robotic system. Our approach based on synergy theory exploits that the follow-up lower limb joint trajectory, i.e. limb intention, could be generated by joint angles of the previous swing process of upper limb which were acquired from Kinect platform, an advanced computer vision platform for motion tracking. A customize Kinect-Treadmill data acquisition platform was built for this study. With this platform, data acquisition on ten healthy subjects is processed in four different walking speeds to acquire the joint angles calculated by Kinect visual signals of upper and lower limb swing. Then, the angles of hip and knee in one side which were presented as lower limb intentions are predicted by the fore angles of the elbow and shoulder on the opposite side via a trained LSTM model. The results indicate that the trained LSTM model has a better estimation of predicting the lower limb intentions, and the feasibility of Kinect visual signals has been validated as well.

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Section: Introductionmentioning

confidence: 99%

An LSTM-Based Prediction Method for Lower Limb Intention Perception by Integrative Analysis of Kinect Visual Signal

Guo

Shao

et al. 2020

Journal of Healthcare Engineering

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Kinect-based 3D Human Motion Acquisition and Evaluation System for Remote Rehabilitation and Exercise

You

Wang

Osawa

et al. 2022

2022 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)

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Development of a Tele-Rehabilitation System Using an Upper Limb Assistive Device

Tanaka

Lian²,

Liao³

et al. 2021

JRM

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A tele-rehabilitation system that can achieve remote interaction between a physical therapist (PT) and a patient was developed. Patients need to execute rehabilitation exercises to maintain upper limb function. However, it is difficult for them to travel to hospitals without aid. This system is equipped with a PC and a Kinect sensor at the hospital side (i.e., the PT), and a PC and an upper limb assistive device in the patient’s home. The PT displays the motion in front of a Kinect sensor, which identifies the motion. In addition, the device on the home side assists the motion of the patient using the Internet. When the device receives a force higher than the safety value from the patient at any particular point on it, vibrators at the corresponding point on the PT’s arm start to vibrate. Thereby, the PT can identify the patient’s condition and limitations. The time delays in the transmission of data of device motion and the vibrators were measured and compared. As a result, the PT could identify the patient’s condition faster than the motion of the device.

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Development and Evaluation of a Kinect-Based Motion Recognition System based on Kalman Filter for Upper-Limb Assistive Device

Cited by 6 publications

References 9 publications

An LSTM-Based Prediction Method for Lower Limb Intention Perception by Integrative Analysis of Kinect Visual Signal

An LSTM-Based Prediction Method for Lower Limb Intention Perception by Integrative Analysis of Kinect Visual Signal

Kinect-based 3D Human Motion Acquisition and Evaluation System for Remote Rehabilitation and Exercise

Development of a Tele-Rehabilitation System Using an Upper Limb Assistive Device

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