Biofeedback Retention in Individuals With AKA

Summary

More than two million Americans are currently living with a full or partial limb loss, and an additional 185,000 amputations occur each year. The majority of amputations occur in the lower limbs. There are many potential causes for amputation, but the majority can be attributed to vascular diseases, such as diabetes, traumatic injury, and cancer. For these individuals, prosthetic devices play an important role in restoring mobility and enabling them to participate in everyday activities. However, when learning to use these devices, patients often alter their movement patterns to compensate for pain or discomfort, a decreased ability to feel what their prosthetic limb is doing, and/or a fear of falling. By changing their movement patterns, patients will tend to am their intact leg, which has been shown to lead to long-term joint damage and chronic injury. For perspective, 75% of United States veterans living with amputation are diagnosed with a subsequent disease affecting their muscle, bone, and/or joint health. Therefore, therapy sessions, known as gait retraining, are an integral part of teaching prosthesis users to walk in a safe and efficient manner.

With recent advances in wearable technology, researchers and therapists have begun exploring the use of biofeedback systems to assist with this retraining. In these systems, wearable sensors are used to measure how the patient is moving in real-time, and can provide information on how much time they spend on each leg and how much each joint moves during walking. Biofeedback refers to the process of communicating the information from these sensors back to the patients instruct them whether they need to change their movements. Previous research has shown that these systems have excellent potential for helping patients with physical disabilities improve their quality of motion. However, relatively little research has explored how well individuals with above-knee leg amputations respond to biofeedback during gait retraining. Importantly, the question of whether the new movement patterns taught using biofeedback will persist after training has finished remains unanswered.

Therefore, the primary objective of this research is to determine whether biofeedback is a feasible tool for gait retraining with above-knee prosthesis (including a prosthetic knee, ankle, and foot) users. To answer these questions, forty individuals currently using above-knee prosthetic systems will undergo a single session of biofeedback training. Half of these populations will be from the civilian population, and half will be military veterans. During this training, the biofeedback system will apply short vibrations - similar to those generated by cellphones - to their skin every time that the patient reaches the desired degree of hip rotation during walking. Participants will be instructed to keep increasing their hip motion until they feel a vibration on every step. Before training, they will be instrumented with a wearable motion captures system, pressure sensors embedded in their shoes, and a wearable heart rate monitor. Using these devices, researchers will measure the participants' walking patterns without biofeedback determine their current ability. Once training is complete, their walking patterns will be measured again, first while using the biofeedback system, and then again fifteen minutes and thirty minutes after the biofeedback system has been removed. The data measured during these tests will enable researchers to calculate functional mobility scores that are used to evaluate the quality of a patient's walking, and then compare how these scores change before, during, and after biofeedback training.

The knowledge gained through this research constitutes a critical step towards identifying optimal biofeedback strategies for maximizing patient mobility outcomes. The findings will be essential for the development of gait retraining protocols designed to reduce the incidence of chronic injury, and enable patients to achieve their full mobility potential. Building on these results, the next research phase will be to incorporate biofeedback training into a standard six-week gait retraining protocol to evaluate its long-term effectiveness as a rehabilitation tool. Unlike traditional gait retraining, which requires patients to visit clinics in-person for all sessions, the wearable, automated nature of biofeedback training will allow patients to continue gait training from home. This ability will enable patients to continue training activities between sessions, and ultimately may be able to substitute for some in-person visits. This potential for remote therapy has exciting implications for improved access to care for individuals living long distances from their rehabilitation providers, or those suffering from social anxiety, as well as during global health pandemics where in-person visits are difficult.

Conditions

• Amputation of Knee
• Back Pain
• Osteo Arthritis Knee

Interventions

DEVICE

Haptic Biofeedback from SageMotion Biofeedback System

Haptic biofeedback units ("vibrating motors") will be placed on individual body segments. The haptic biofeedback system will be configured to provide vibratory stimuli when a target minimum hip extension angle is reached during the loading response. The minimum threshold will be determined by the therapist based on the patient's current ability. Specifically, the system will target a 10-20% increase in extension angle from their current level, as identified by the therapist. A vibration stimulus will be first applied each time this minimum angle is achieved, and will continually increase in intensity in proportion to the degree with which the patient exceeds this minimum value. The stimuli will stop being applied when the extension angle drops back below the threshold. These intensity-modulated stimuli have been selected to encourage the patient to exceed the minimum threshold rather than stop extending when the stimulus is first applied

Sponsors & Collaborators

• University of California, San Francisco

  collaborator OTHER

• VA Palo Alto Health Care System

  collaborator FED

• San Jose State University

  lead OTHER

Study Design

Allocation

NA

Purpose

BASIC_SCIENCE

Masking

NONE

Model

SINGLE_GROUP

Eligibility

Min Age

18 Years

Max Age

70 Years

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2021-09-15

Primary Completion

2024-09-14

Completion

2024-09-14

Countries

• United States

Study Locations