Walking Speed
A widely studied measure of mobility and functional performance that may change with disease, injury, and aging.
RESEARCH & DEVELOPMENT
Gait is more than the way we walk. It reflects the interaction of the nervous system, muscles, joints, balance, and overall physical function.
GaitMate's research explores how wearable sensing and digital analysis could help characterize changes in movement, support rehabilitation, and investigate opportunities for preventive care.
THE IMPORTANCE OF GAIT
Walking is a complex process requiring coordination between the brain, spinal cord, peripheral nerves, muscles, and musculoskeletal system.
Changes in walking speed, step length, symmetry, balance, and movement variability can provide information about physical function and, in some settings, neurological health.
Because many of these changes emerge gradually, repeated measurements may help researchers understand how movement evolves over time. Wearable technology offers a potential way to collect movement information outside traditional laboratory or clinical environments.
Gait Symmetry
Differences between left and right movement patterns may help characterize compensatory movement or impaired function.
Gait Variability
Changes in the consistency of steps and movement patterns can be relevant to balance, neurological function, and mobility research.
CLINICAL RESEARCH DIRECTIONS
Although GaitMate began with ankle rehabilitation, our long-term research interests extend to conditions in which altered gait, mobility, or balance is an important clinical feature.
These are proposed research directions rather than validated applications of the current GaitMate system.
Parkinson's Disease
Parkinson's disease can affect walking speed, stride length, turning, and movement initiation. Some individuals experience freezing of gait, in which forward movement becomes temporarily difficult.
Future GaitMate research could investigate how wearable movement measurements characterize changes in gait over time.
Multiple Sclerosis
Multiple sclerosis can affect walking ability, balance, coordination, and endurance. Walking speed and other mobility measures are already used in research and clinical assessment of the condition.
GaitMate could explore complementary longitudinal movement monitoring, building on existing approaches.
Stroke Rehabilitation
Stroke can lead to weakness, asymmetric walking patterns, altered balance, and changes in weight distribution.
Future wearable systems could investigate gait symmetry, postural sway, and movement progression during rehabilitation.
Traumatic Brain & Spinal Cord Injury
Traumatic brain injury can affect balance, coordination, and walking performance. Spinal cord injury may impair motor control, strength, sensation, and mobility.
Future research could investigate condition-appropriate wearable measurements to support movement assessment and rehabilitation tracking.
Cerebral Palsy
Cerebral palsy can affect muscle tone, posture, coordination, and gait. Walking patterns vary considerably between individuals.
Wearable monitoring could be investigated as a complementary method for studying functional movement outside structured assessments.
Duchenne Muscular Dystrophy
Duchenne muscular dystrophy causes progressive muscle weakness and may produce characteristic compensatory walking patterns, including a waddling gait.
Future research could explore how noninvasive movement measurements relate to changes in mobility and functional performance.
Fall-Risk Assessment
Changes in walking speed, balance, step variability, and mobility may contribute to fall-risk assessment in older adults.
GaitMate's long-term vision is to investigate whether combinations of wearable movement features could help identify elevated fall risk before a fall occurs.
Injury Recovery
Musculoskeletal injuries can produce pain-related compensation, altered loading, and asymmetrical movement.
GaitMate's initial ankle rehabilitation research provides a starting point for investigating future applications across other joints and injuries.
INITIAL RESEARCH
GaitMate originated as a wearable biosensing concept focused on lateral ankle sprain rehabilitation.
Lateral ankle sprains commonly involve the anterior talofibular ligament (ATFL), with the calcaneofibular ligament (CFL) and posterior talofibular ligament (PTFL) also relevant to lateral ankle anatomy and more extensive injuries.
Our initial research investigated how localized wearable measurements might help characterize mechanical changes around these ligament regions during movement and rehabilitation.
The proposed nine-sensor architecture uses three sensing locations associated with each ligament region. This is a conceptual placement strategy, not yet a validated method for directly measuring ligament strain.
Anterior Talofibular Ligament
Frequently involved in lateral ankle sprains and a major focus of the initial concept.
Calcaneofibular Ligament
Contributes to lateral ankle stability and is included in the proposed sensing-region design.
Posterior Talofibular Ligament
Part of the lateral ligament complex and included in the initial multi-region sensing concept.
CURRENT DEVELOPMENT
GaitMate is currently progressing through early hardware and software development. Our work focuses on evaluating candidate sensors, refining wearable architecture, and developing tools to process and visualize movement-related data.
Sensor Exploration
Comparing stretch, strain, inertial, and muscle-activity sensing modalities for potential wearable monitoring.
Hardware Prototyping
Building early electronic prototypes and evaluating sensor response to movement and orientation.
Wearable Integration
Investigating sticker construction, adhesive materials, sensor placement, and compact electronics integration.
Software Development
Developing application interfaces, data visualization, movement-event detection, and rehabilitation feedback.
Bench Testing
Planning controlled tests of sensor response, repeatability, noise, stability, and mechanical performance.
Future Validation
Designing future studies to assess measurement accuracy, movement characterization, and condition-specific use.