Optimizing Transhumeral Osseointegration Prosthesis Control
Abstract
Our research will address the PRORP Clinical Translational Research Award Focus Area: Prostheses and Orthoses: development of high-performance prosthetic devices designed to enhance whole person performance in patients with limb amputation. We will optimize outcomes from osseointegration after above-elbow (transhumeral) amputation by investigating a custom press-fit osseointegration implant and developing a new control strategy to drive the prosthesis movements. Limb amputation has been an unfortunate hallmark of military conflict. Many Service Members have suffered traumatic arm amputations. Loss of an arm leads to severe limitations in function. Even when provided with an appropriate prosthetic limb, people with arm amputation rely on the remaining arm to perform activities of daily living far more than using the prosthesis. When the arm amputation includes loss of the elbow joint, function becomes even more limited. Many patients choose not to wear a prosthesis because it is difficult to control the prosthetic joints. Furthermore, the prosthesis is traditionally attached to the remaining limb through a hard socket that squeezes the soft tissues and then is strapped across the chest or to the other shoulder. This setup restricts the ability to move the shoulder to position the prosthetic arm to accomplish tasks. Newer surgical techniques insert a titanium rod into the remaining bone with a metal attachment that comes through the skin and allows a direct connection of the prosthesis to the bone. This technique is called osseointegration and is becoming more available in the United States and worldwide. There is evidence that osseointegration for the lower limb (above the knee) amputation is beneficial. However, upper limb osseointegration is less studied. Osseointegration could dramatically impact Service Members with above-the-elbow amputation by removing the need for a socket, providing secure attachment and suspension of the prosthesis directly to the bone, and providing better control and sensation of where the prosthetic limb is in space. Our research will address the main barriers to advancing transhumeral osseointegration to clinical care. First, we will apply new machine-learning strategies to improve the ability to use surface muscle signals to control the prosthesis. Current upper limb prostheses suffer from not being reliable to control when the arm is moved in different positions -- for example, reaching to grasp a cup off a shelf. The lack of reliable control is a frustration for many prosthesis users, that we will solve. Secondly, we will develop and deploy virtual reality training tools for people to train at home during their recovery after surgery. These tools will make rehabilitation more accessible and convenient for those that have difficulty accessing the clinic, and improve the transition to using the prosthesis. Lastly, we will provide detailed evidence on outcomes from the osseointegration and our new control algorithm in a clinical trial. We hypothesize that our intervention will improve active prosthesis usage in daily life, reduce abnormal movement compensations and improve function when using the prosthesis. These factors will ultimately improve satisfaction and quality of life for those with arm amputation. This work will have an immediate impact by providing new control strategies for upper limb prostheses that can be used for persons with limb loss, even if still using a socket prosthesis. We will also provide crucial evidence on the efficacy and safety of the press fit osseointegrated implants for the upper limb, which have not yet been reported. In the long term, this evidence will improve the options available for prosthetic arm restoration and reduce long-term complications for persons with traumatic arm amputation.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 04, 2024
- Source ID
- HT94252310398
Entities
People
- Jacqueline S Hebert
Organizations
- United States Army
- University of Alberta