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Completed

NCT Number: NCT02888483

PEAKS: Validation of Mobile Technologies

The overall objective of this project is to evaluate and validate the accuracy and usability of a deployed beta sensor-based system. This is a cross-sectional validation study of 100 apparently health community dwelling adults aged 60+ years. Participants will perform standardized lifestyle, exercise and sedentary type physical activities in a clinic laboratory and home setting.

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Key information

Age range

60 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

UF Institute on Aging Clinical and Translational Research Building

Gainesville, Florida, 32611, United States

About this study

Wearable activity monitors have the potential to continuously and objectively measure physical activity. However, existing monitors do not address the unique challenges that face older adults, who comprise the largest segment of population who suffer from physical disabilities and dexterity issues that can make using such monitors exceedingly difficult. In fact, the majority of wearable devices on the market address the needs of three broad segments:

  • Consumers: these devices are designed and optimized for motivated, healthy younger individuals and require pairing with smartphones to transmit data, while restricting or, at best, limiting access to raw data and algorithms.
  • Researchers: research-focused devices tend to be validated across a wide range of studies, but are not optimized for wearability or longitudinal use.
  • Developers: Developer-focused devices typically provide high configurability, a high- definition screen, and a variety of sensors (e.g. accelerometer, gyroscope, air pressure, light, temperature, etc.) that are suited for research and development, but are not optimized for power-efficient use.

To overcome the barriers that existing monitors impose on measuring free-living physical activity data, EveryFit developed in-home activity monitoring technology that addresses the specific and unique needs of the older population (incorporated in product called QMedic).

The overall objective of this project is to evaluate and validate the accuracy and usability of a deployed beta sensor-based system. The technology utilizes novel power-efficient engineering to continuously measure physical activity (including intensity, type and duration) in both laboratory and free-living settings. To accomplish this objective we will enroll 100 adults 60+ years of age who will perform standardized lifestyle, exercise and sedentary type physical activity in the laboratory. A subset of participants will also be asked to wear the monitor in free-living settings.

The proposed work can have far-reaching impact given the growth in the older adult population, which suffers disproportionally from chronic disease and functional impairments. Validating technology that measures physical activity continuously and accurately at the home is a critical step in scaling the system, conducting affordable population- scale studies, and maximizing the societal impact of the innovation.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Age 60+ years old
  • Community dwelling adults without significant health issues that would impact safety of participation
  • Willingness to undergo all testing procedures
  • Weight stable for at least three months
  • Able to understand and speak English

Exclusion criteria

  • Failure to provide informed consent
  • Use of walker (use of a cane is permitted)
  • Lower extremity amputation
  • Develops chest pain or severe shortness of breath during physical stress
  • Post-stroke syndrome causing ambulatory deficits (other stroke survivors permitted)
  • Needs assistance with basic activities of daily living: feeding, dressing, continence, bathing, toileting, and transferring from a bed to a chair or from a chair to walking
  • Lives in a nursing home; persons living in assisted or independent housing are not excluded
  • Heavy drinking as drinking 5 or more drinks on the same occasion on each of 5 or more days in the past 30 days.
  • For women who are child-bearing age (up to 62 years of age): pregnancy or breast-feeding
  • Participation in a structured weight loss program or fad diet in the last month
  • Weight reduction surgery in the past year
  • Known neuromuscular disorder that restricts activity (e.g. Rhabdomyolysis, Myasthenia Gravis, Ataxia, Apraxia, post-polio syndrome, mitochondrial myopathy, etc.)
  • Diagnosed neuropathy that causes pain that restricts activity
  • Symptomatic peripheral arterial disease that restricts activity
  • Unable to communicate because of severe hearing loss or speech disorder
  • Severe visual impairment, which would preclude completion of the assessments
  • Progressive, degenerative neurologic disease (e.g., Parkinson's Disease, Multiple Sclerosis, ALS)
  • Severe rheumatologic or orthopedic diseases that significantly restricts activity (e.g., awaiting joint replacement, active inflammatory disease)
  • Terminal illness, as determined by a physician
  • Severe pulmonary disease, requiring the use of supplemental oxygen or steroid therapy
  • Severe cardiac disease, including NYHA Class III or IV congestive heart failure, clinically significant aortic stenosis, recent history of cardiac arrest, use of a cardiac defibrillator, or uncontrolled angina
  • Other significant comorbid disease discovered during medical screening that would elicit safety concerns, (e.g. renal failure on hemodialysis, psychiatric disorder, chronic fatigue syndrome, etc.)
  • Pacemakers and implanted cardiac defibrillators

Treatment and study plan

Primary outcomes

  1. Metabolic equivalent (MET) value

    Time frame: within one month

    MET value of physical activities defined as the oxygen uptake (VO2 = milliliter• min-1•kg-1) during a steady state rate expressed as a function 3.5 milliliter• min-1•kg-1.

Secondary outcomes

  1. Tradeoff Accuracy in metabolic equivalent estimation and power consumption

    Time frame: within one month

    We will manipulate the state machine that samples data from the device with different duty cycles based on contextual changes as measured by the accelerometer or classified by models that use the accelerometer data to classify behavior or categories of behavior.

Sponsors and collaborators

Lead sponsor

University of Florida

Other

Collaborators

  • EveryFit, Inc
  • National Cancer Institute (NCI)
  • National Institute on Aging (NIA)

Registry information

Official study title

PEAKS: Validation of Mobile Technologies for Clinical Assessment, Monitoring and Intervention

Acronym: PEAKS

Important dates

Study start
2016
Primary completion
2018
Study completion
2018
First posted
Sep 5, 2016
Registry last updated
May 13, 2019

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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