BrainRobotics Prosthetic Hand

Background of Invention

BrainRobotics?is a company founded in 2015 by Harvard graduates and developed in the Harvard Innovation Lab.?BrainCo, the parent firm, is the only one to have created BMI (brain/machine interface) applications in prostheses and cognitive wellness/training. The firm grew to 150 employees globally, making it one of the world’s largest, if not the largest, BMI companies. After years of research and development,?BrainCo?engineers developed the?BrainRobotics?Prosthetic hand, allowing people with various upper limb disabilities to employ cutting-edge technology to operate a prosthetic hand with muscle impulses.

Device Description

With anti-slip technology, the?BrainRobotics?Prosthetic hand features ten freely adjustable joints and digits that move independently. In addition, the wrist is well-integrated, with 180-degree manual rotation. A powered thumb with active adduction, abduction, flexion, and extension capabilities is also included on the hand. There are 24 gestures available and a buzzing and vibrating feature. Additionally, the program will run on both iOS and Android smartphones. The hand dimensions are: 183 mm in length x 86 mm in width and a weight of 530 grams, with an opening speed of 0.4 seconds.

Product Application

Thousands of Americans have lost their limbs during combat in recent wars, and hundreds have had multiple limbs amputated. Stress, depression, anxiety, and post-traumatic stress disorder frequently exacerbate physical disability. Therefore, a technological breakthrough that restores physical capacity and independence to individuals who have lost it would be a game-changer for these patients. The AI-powered prosthetic hand that learns from repeated motions allows hand amputees to perform an infinite variety of grips and gestures.?

Unique AI Features

Compared to traditional prosthetics that depend only on electromyography (EMG), Artificial Intelligence (AI) elevates these prosthetic hands to new heights. EMG measures muscular electrical activity in response to a nerve’s stimulation to move the hand. Although the new prostheses still use EMG, the inclusion of AI improves their performance significantly. Machine learning (ML) hand recognizes the user’s recurrent patterns and, over time, refines the intelligence built into the hand, allowing hand control to become more closely aligned with the user’s usage habits and demands.?