Smart Home-based Technology to Promote Functional Mobility Among Individuals With Parkinson's Disease

People with Parkinson's disease (PwP) may experience severe difficulties in mobility that negatively affect their function and Quality of life. Freezing of gait, (FOG) is a brief and sudden inability to initiate walking or move forward, despite an intention to walk. Such episodes are often observed when PwP attempt to turn, cross a narrow space or negotiate obstacles. Rehabilitation interventions for FOG represent the most effective non-pharmacological approach to maintain functional independence and reduce the risk of falls. A key approach is the provision of external cues, defined as sensory stimuli, which facilitate gait initiation and continuation. These external cues are suggested to bypass the dysfunctional movement pathways in the basal ganglia and therefore, are considered effective in alleviating FOG. Cueing can be applied by different modalities; the most common are visual (e.g. spaced lines on the floor) and auditory (e.g. rhythmic metronome beats).

The term smart-home refers to a range of technologies that are designed for and deployed in individual residences, and are equipped with non-invasive, environmental, and physiological sensors. The concept of a "health smart-home" is a variation of smart-home with a focus on assistive technologies to enable the independence and wellness of residents, including the elderly and patients in supervised residences.

In this study, the investigators will be testing the first phase of developing a smart-home technology designed for patients coping with PD to use in their homes and aims to improve gait and assist in prevention of FOG. The aims of this exploratory study are to evaluate the 1) practical feasibility of the technology, 2) patient satisfaction and 3) the effect of the technology on gait. The device was developed by Selfit medical© and included application of light stripes (visual cues) and metronome beats (auditory cues) that are individually adjusted to the participant walking parameters.