Exoskeletons, Human Intention
Conditions
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
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.
Interventions
OTHERA 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.
Sponsors
National Taiwan University Hospital
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
BASIC_SCIENCE
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to 80 Years
Healthy volunteers
Yes
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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| 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. |
Countries
Taiwan
Contacts
Primary ContactWei-Li Hsu, Ph.D
Outcome results
None listed