A Digital Twin for Exoskeleton Pilot

Not Applicable

Recruiting

• Conditions: Human Intention; Exoskeletons
• Interventions: Other: A Digital Twin for Exoskeleton Pilot

• Registration Number: NCT05650255
• Lead Sponsor: National Taiwan University Hospital

Brief Summary

Although exoskeletons have been studied for many years, actual products have been sold on the market. However, there are still many limitations in the practical application of exoskeletons, and the control logic is also limited to the level of motor torque compensation, and lacks the consideration of overall motion stability (such as whether the wearer (driving, pilot) will fall). The purpose of this project is to establish a digital twin of this driving, which will perform the driving action in parallel, and calculate in parallel in the virtual environment the torque required to provide each joint torque to maintain stable walking without falling, and this torque can be used as a monitoring basis for the auxiliary torque of each axis for the exoskeleton. When the exoskeleton's movements are out of range of a stable gait, the controller can warn and attenuate the output of auxiliary forces, and on the other hand, it has the opportunity to analyze whether the intention of driving is to switch the movement mode - such as stopping, or sitting, squatting, etc.

Detailed Description

Not available

Basic Information
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Recruitment & Eligibility
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Study & Design
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Trial Locations

Study Timeline

• Study Start: 2022-11-07
• Study First Submitted: 2022-11-27
• Study First Submitted QC: 2022-12-06
• Study First Posted: 2022-12-14
• Status Verified: 2023-08
• Last Update Submitted: 2024-01-15
• Last Update Posted: 2024-01-17
• Primary Completion: 2025-07-31
• Study Completion: 2025-10-31

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 30

Inclusion Criteria

1. Can stand independently and walk for more than 5 minutes.
2. According to age, it can be divided into: elderly groups (aged between 50~80 years old); Young people (aged 20~50 years).

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Exclusion Criteria

1. Have current or previous neurological diseases of the lower extremities, such as: acute neuritis, stroke, Parkinson's disease.
2. Have current or previous orthopedic diseases of the lower extremities, such as: knee replacement, rheumatoid arthritis, or sports injuries and other symptoms.

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Study & Design

• Study Type: INTERVENTIONAL
• Study Design: SINGLE_GROUP

Arm && Interventions

Group	Intervention	Description
A Digital Twin for Exoskeleton Pilot	A Digital Twin for Exoskeleton Pilot	This project is expected to use different machine learning models to make accurate predictions of human intent when healthy people drive different actions or action transitions of common human actions. Drivers will wear sensors such as inertial measurement unit (IMU) and electromyography (EMG) in the lower limbs to measure body signals of participants during actions in a non-invasive way, and let the system calculate the joint angle, angular velocity and angular acceleration of each joint of the driving lower limb related human signals.

Primary Outcome Measures

Name	Time	Method
The angles of the subject's joints.	3 years	The angles of the subject's joints (unit: degree) are performed by using IMU sensors when subjects do some action such as standing, walking or sitting.
The activities of muscles state of human movement.	3 years	The activities of muscles state of human movement (unit: millivolt or %) are performed by using EMG sensors when subjects do some action such as standing, walking, sitting, squatting or step-up.
The comprehensive intention of the subjects.	3 years	The comprehensive intention time of the human body (unit: second) is performed by using IMU sensors and EMG sensors when subjects do some action such as standing, walking, sitting, squatting or step-up.

Trial Locations

Locations (1)

National Taiwan University Hospital; 🇨🇳 Taipei,Taiwan, Taiwan