Exploring the Effectiveness of Sensor-based Balance Training on Patient Outcome Measures

Explore the benefit of the game-based virtual reality system in improving lower extremity kinematics and balance in patients suffering from disease/disorders including Diabetes, Cancer, Multiple Sclerosis, Arthritis, Parkinson's disease, Cognitive Disorders, Brain Injury, Stroke or Frailty. A four to six weeks of training with 2 training session/week will be provided.

Individuals suffering from certain disorders/diseases including diabetes, arthritis, cancer, osteoarthritis, stroke, Parkinson's disease, cognitive impairment or brain Injury are more likely to experience a fall or a fall-related injury than healthy individuals during to impaired postural stability or diminished joint perception. Under certain circumstance they may also experience pain, depression, anxiety, and a decreased quality of life. The investigators' research has been designed to provide exercise training using non-invasive body-worn sensors (similar to those used in an iPhone®) to provide real-time visual information about joint motion in a virtual environment. These sensors will be worn using a vest, t-shirt or elastic band. The investigators will, 1) assess changes in participant's perception of lower extremity position while they perform these exercises; 2) motivate and guide simple exercise performance in the clinic/home, using an interactive game-like scheme; and 3) assess changes in participant's postural stability and gait as a result of provided exercise training. The information gathered will provide new understanding about more helpful rehabilitation strategies that improve postural stability in patient population.

Diabetes, Cancer, Multiple Sclerosis, Arthritis, Parkinson's Disease, Cognitive Disorders, Brain Injury, Stroke

inertial sensor based system (wearable sensors, LEGSys, Biosensics LLC) will be used for balance training with computerized feedback. The balance training program is focused on lower extremities including ankle joint exercise and virtual obstacle crossing tasks.

The control group will ask to perform a home based program includes similar exercise components as proposed in the experimental group, however without computerized feedback. Exercises include postural balance tasks, such as backward and forward weight shifting, as well as dynamic balance exercises, such as marching in place (comparable to virtual obstacle crossing in experimental group).

Subjects will perform progressive and computerized foot and ankle exercises which include weight shifting, ankle reaching task while standing, and virtual obstacle crossing task (i.e. balancing on single leg) using wearable sensors technology (Exergaming) equipment). Subjects will perform these exercises for 4-6 weeks, twice per week. The duration of exercise per session is anticipated to be 30-45 minutes.

Subjects in the control group will ask to perform a standard home based balance program for 4-6 weeks. The home based program includes similar exercise components as proposed in the experimental group, however without computerized feedback and Exergaming equipment.

Balance will be quantified by measuring area of sway of center of mass (with unit of cm2) during quite standing according to Romberg's protocol and using validated instrument (BalanSens, Biosensics, MA, USA)

Gait Speed (with unit of m/sec) will be measured using validated wearable technology (LEGSys, Biosensics, MA, USA) and during walking with habitual and fast speed walking

Stride Length (with unit of meter) will be measured using validated wearable technology (LEGSys, Biosensics, MA, USA) and during walking with habitual and fast speed walking

Stride time (with unit of second) will be measured using validated wearable technology (LEGSys, Biosensics, MA, USA) and during walking with habitual and fast speed walking

Average of walking steps (no unit) per day will be measured during 48 hours of daily physical activity monitoring using a validated wearable sensor technology (PAMSys, Biosensics, MA, USA)

Daily average of walking bout (continuous walking without stop, with unit of steps) will be measured over 48 hours monitoring of physical activity using a validated wearable sensor technology (PAMSys, Biosensics, MA, USA)

Daily average of standing bout (continuous standing without changing in posture with unit of seconds) will be measured over 48 hours monitoring of physical activity using a validated wearable sensor technology (PAMSys, Biosensics, MA, USA)

Daily average of longest walking bout (longest continuous walking without stop per day, with unit of steps) will be measured over 48 hours monitoring of physical activity using a validated wearable sensor technology (PAMSys, Biosensics, MA, USA)

Inclusion Criteria: Diagnosis of: diabetes cancer multiple sclerosis arthritis Parkinson's disease cognitive disorders brain injury frailty stroke Exclusion Criteria: conditions not related to specific disorders affecting balance and gait