A Highly Efficient HMI Algorithm for Controlling a Multi-Degree-of-Freedom Prosthetic Hand Using Sonomyography.

Area of Science:

• Biomedical Engineering
• Rehabilitation Technology
• Human-Machine Interfaces

Background:

• Sonomyography (SMG) uses ultrasound to monitor muscle activity for prosthetic control.
• SMG shows promise as an alternative to electromyography (EMG), achieving high accuracy in hand gesture classification.
• Limited studies have integrated SMG with prosthetics for real-world testing on amputees.

Purpose of the Study:

• To develop and evaluate an efficient human-machine interface algorithm for controlling a 6-DOF prosthetic hand using a wireless, wearable ultrasound probe.
• To assess the accuracy and reliability of the SMG system in classifying hand gestures.
• To demonstrate the system's effectiveness in assisting amputees with daily activities.

Main Methods:

• Developed a novel human-machine interface algorithm for prosthetic hand control.
• Utilized a wireless and wearable ultrasound imaging probe for monitoring forearm muscle activity.
• Conducted offline gesture classification tests with healthy participants and real-time functional tests with amputees.

Main Results:

• Offline testing achieved 100% accuracy in classifying nine distinct hand gestures among healthy participants.
• Real-time experiments demonstrated the prosthetic hand's ability to assist amputees in performing various daily tasks.
• The SMG system proved effective in controlling a 6-DOF prosthetic hand.

Conclusions:

• The developed SMG system provides a highly accurate and reliable method for controlling upper-limb prosthetics.
• This technology shows significant potential for improving the functional independence of amputees in daily life.
• SMG represents a viable and advanced alternative to traditional prosthetic control methods like EMG.