ACTIVESTEP FALL PREVENTION TRAINING SYSTEM

Award Information
Agency:
Department of Health and Human Services
Branch
n/a
Amount:
$782,381.00
Award Year:
2007
Program:
SBIR
Phase:
Phase II
Contract:
2R44AG023407-04
Award Id:
71054
Agency Tracking Number:
AG023407
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
Simbex, Llc, 10 Water Street, Lebanon, NH, 03766
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
015704559
Principal Investigator:
RICHARD GREENWALD
(603) 448-2367
RGREENWALD@SIMBEX.COM
Business Contact:
RICHARD GREENWALD
(603) 448-2367
thays@simbex.com
Research Institution:
n/a
Abstract
DESCRIPTION (provided by applicant): Falls are a leading cause of injury and mortality in the elderly. Ongoing research using the ActiveStep treadmill completed in Phase I/Phase II, has demonstrated that a treadmill-based perturbation tool for tripping an d slipping has demonstrated a positive effect on the biomechanical performance of older adults subject to laboratory induced trip and slip disturbances. The proposed ActiveStep system provides the enabling technology for large- scale application of clinica lly relevant fall prediction and prevention training. Use of ActiveStep is hypothesized to reduce the incidence of falls, the leading cause of injury deaths among people over 65 years old. The Principal Objective of this NIH Phase II Competing Renewal SBIR project is to continue and complete product development efforts for and clinical validation of ActiveStep, a treadmill- based rehabilitation device for fall prevention training and fall risk assessment for older adults. The design goals are to reduce the cost of goods for manufacturing and to meet electrical and mechanical safety requirements and life-cycle testing that are included in national and international standards for commercial exercise equipment. At the same time, we propose to continue pre-marke t approval clinical studies for required regulatory pathways to assess the efficacy of our fall assessment algorithm and our fall prevention training protocol. The proposed ActiveStep system provides the enabling technology for large-scale application of c linically relevant fall prediction and prevention training. Use of ActiveStep is hypothesized to reduce the incidence of falls, the leading cause of injury deaths among people over 65 years old. Hip fractures account for about 60% of fracture related hospi talizations with 90% of hip fractures resulting from falls. Recent research using a novel quasi-prospective study design indicates that lower extremity strength and power and measures of static and quasi-static balance do not predict risk of trip-related f alls by older adults. In contrast, existing research has shown that repeated exposures to a slip or trip distance can reduce the probability of falling. If technically and economically feasible, ActiveStep will help reduce the health care costs associated with the treatment and rehabilitation of injuries sustained during a fall.

* information listed above is at the time of submission.

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