We propose to address two important public health quality of life concerns - fall prevention and frailty in older adults by developing an accurate wearable sensor technology that more accurately characterizes physical activity, risk of falling and early indicators of frailty. In Phase I of this STTR project, we developed a unique platform (PAMSysTM: Physical Activity Monitoring System) for objective measurement of physical activity during everyday living and demonstrated the proof of concept of the PAMSysTM platform for objective assessment of spontaneous daily physical activity, risk of falling and activity organization among older adults. In Phase II of the project, we propose two additional clinical studies to further evaluate the clinical applications of the PAMSysTM platform and to continue our research and development efforts to transform the PAMSysTM platform into a clinimetrically sound low-cost tool for remote screening of risk of falling and early detection of frailty. We will enhance our technology for early diagnosis and remote monitoring of the risk of falling/frailty using non-invasive physical activity telemonitoring. Using this technology we will identify patterns indicative of risk of falling and for early detection and intervention of the increasingly important geriatric syndrome of frailty in at-risk elders. In addition, it will enable remote and continuous screening of the risk of falling during activities of daily living, supportin autonomy and quality of life, and limiting the need for burdensome face to face clinical assessment. The proposed technology can also provide an objective tool to evaluate physical activity decrements and to help prescribe and measure the effects of rehabilitation and treatment strategies on reductions in the risk of falling based on the relative efficacy of clinimetrically relevant interventions. Taken together, these considerations support the urgent need to: a) develop instrumentation for objective assessment of the frequency, duration and organization of physical activity among older adults at risk of falling or developing frailty, and ) develop instrumentation that is ambulatory and low burden, thus allowing the assessment of naturalistic patient movement in everyday life (outside of the artificial lab environment). We will pursue these goals by: a) investigating the degree to which the parameters gathered by the PAMSysTM platform are sensitive to changes in daily physical activity that occur as a result of frailty, b) by examining the degree to which changes in PAMSys-derived variables of activity and movement correspond with changes in geriatric- assessed functional capacity measures, and self-reported disability, history of fall, risk of falling, and frailty;c) by improving current sotware algorithms to allow assessment of fine-grained movement parameters sensitive to early diagnosis of frailty and risk of falling, and e) by modifying the design of our sensor for real-tim wireless data transfer.

Public Health Relevance

As baby boomers age, and their expected life span increases, the number of U.S. elders aged 65 and over will dramatically rise, producing unprecedented need for effective, low cost monitoring and treatment of home and community-dwelling elders. This study aims to develop and commercialize a novel wearable technology for tele-health activity monitoring of elders using a single and easily wearable sensor. The proposed technology allows remote and continuous linimetrically relevant screening of elder's risk of falling as well as early detection and targeted intervention of those at risk of frailty.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Small Business Technology Transfer (STTR) Grants - Phase II (R42)
Project #
5R42AG032748-03
Application #
8523717
Study Section
Special Emphasis Panel (ZRG1-BBBP-V (10))
Program Officer
Joseph, Lyndon
Project Start
2008-07-01
Project End
2014-06-30
Budget Start
2013-08-01
Budget End
2014-06-30
Support Year
3
Fiscal Year
2013
Total Cost
$444,939
Indirect Cost
Name
Biosensics, LLC
Department
Type
DUNS #
802270988
City
Cambridge
State
MA
Country
United States
Zip Code
02139
Schwenk, Michael; Hauer, Klaus; Zieschang, Tania et al. (2014) Sensor-derived physical activity parameters can predict future falls in people with dementia. Gerontology 60:483-92
Toosizadeh, Nima; Bunting, Matthew; Howe, Carol et al. (2014) Motorized mobility scooters: the use of training/intervention and technology for improving driving skills in aging adults - a mini-review. Gerontology 60:357-65
Schwenk, Michael; Howe, Carol; Saleh, Ahlam et al. (2014) Frailty and technology: a systematic review of gait analysis in those with frailty. Gerontology 60:79-89
Najafi, Bijan; Armstrong, David G; Mohler, Jane (2013) Novel wearable technology for assessing spontaneous daily physical activity and risk of falling in older adults with diabetes. J Diabetes Sci Technol 7:1147-60