Current Research
Balance and Falls
Falls among the elderly and Parkinson's disease populations is the cause of a large source of morbidity and mortality. Falls often lead to serious injuries, long hospital stays, and increased healthcare costs.
The investigation of impaired balance as a cause of an increasing fall risk has been limited to a select few gait parameters such as gait speed and variability in stride timing. These stride to stride fluctuations, or gait variability, have been shown to correlate significantly with the risk of falling in the elderly and in Parkinson's disease populations.
Previous work resulted in a wireless, wearable system developed to measure several relevant gait analysis parameters in an individuals normal environment, in particular, outside the confines of a traditional motion laboratory. The calibrated sensor outputs were analyzed and validated with results obtained simultaneously from The Massachusetts General Hospital Biomotion Lab, and demonstrated that this type of wearable system can be highly capable of detecting heel-strike and toe-off, as well as estimating foot orientation and position.
Presently there is a need for applying a mobile gait analysis method that is capable of providing measurements of a comprehensive set of gait parameters in a Parkinson's population, including but not limited to the traditional stride timing and gait speed, that can be used to detect gait changes in gait stability and variability.
Other parameters that need to be measured and assessed to determine their respective effects on balance and fall risk include variability in stride width and stride length, foot pressure distribution, foot accelerations and velocities, and real time foot range of motion. The device also needs to be able to accurately measure and collect gait data independently of the traditional laboratory setting, to provide a more real-life measurement of gait instability and variability.
Providing mobile comprehensive gait monitoring over extended periods of time outside the lab will facilitate characterization and measurement of balance and falls.