A Digital Twin for Exoskeleton Pilot

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.

Study Overview

• Status: Recruiting
• Conditions: Human Intention; Exoskeletons
• Intervention / Treatment: Other: A Digital Twin for Exoskeleton Pilot

Detailed Description

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.

• Study Type: Interventional
• Enrollment (Estimated): 30
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Wei-Li Hsu, Ph.D; Phone Number: +886-2-3366-8127; Email: wlhsu@ntu.edu.tw

Study Locations

• Taiwan
  • Taipei,Taiwan, Taiwan
    • Recruiting
    • National Taiwan University Hospital
    • Contact: Wei-Li Hsu, Ph.D; Email: wlhsu@ntu.edu.tw

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 16 years to 76 years (Adult, Older Adult)
• Accepts Healthy Volunteers: Yes

Description

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 18~50 years).

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.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Basic Science
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm

Intervention / Treatment

Experimental: 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.

Other: A Digital Twin for Exoskeleton Pilot; 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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
The angles of the subject's joints.	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.	3 years
The activities of muscles state of human movement.	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.	3 years
The comprehensive intention of the subjects.	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.	3 years

Collaborators and Investigators

• Sponsor: National Taiwan University Hospital
• Investigators: Study Director: Wei-Li Hsu, Ph.D, Study Principal Investigator National Taiwan Unversity

Study record dates

Study Major Dates

• Study Start (Actual): November 7, 2022
• Primary Completion (Estimated): July 31, 2025
• Study Completion (Estimated): October 31, 2025

Study Registration Dates

• First Submitted: November 27, 2022
• First Submitted That Met QC Criteria: December 6, 2022
• First Posted (Actual): December 14, 2022

Study Record Updates

• Last Update Posted (Actual): March 25, 2025
• Last Update Submitted That Met QC Criteria: March 17, 2025
• Last Verified: February 1, 2025

More Information

Terms related to this study

• Other Study ID Numbers: 202209051RINB

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No