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Operability and Implementation of a Patient Motion Monitoring System Using Wireless Body Worn Sensors (GFD1)

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ClinicalTrials.gov Identifier: NCT02272933
Recruitment Status : Recruiting
First Posted : October 23, 2014
Last Update Posted : June 4, 2018
Sponsor:
Collaborators:
Texas Tech University
AT&T Research Labs
ACM
Information provided by (Responsible Party):
Texas Tech University Health Sciences Center

Brief Summary:
In this observational study, a motion monitoring system including body-worn sensors, communication portals, data capture system, and algorithms will be tested with geriatric patients in Garrison Geriatric Education and Care Center (Lubbock, TX). The study is part of a long-term effort to improve the quality of life and safety of geriatric patients by using autonomous systems that can alert care givers of mobility issues and falls.

Condition or disease Intervention/treatment Phase
Accidental Falls Gait, Unsteady Device: Smart Slipper Device: Belt-Clip Sensor Not Applicable

Detailed Description:

Medical monitoring systems have become an important area of research and development due to the possibility of allowing improved quality of life and care while reducing overall medical costs.

Significance of the study:

The study is significant because it will allow researchers to understand the efficacy of the autonomous sensor system used with actual residents of a geriatric care center. This study is one of the first attempts to monitor movements of geriatric residents as they go about their activities of daily living. This type of system has the potential to improve the quality of life and safety of geriatric patients.

Goals:

The development of autonomous patient monitoring technologies that will eventually improve the quality of life and safety of patients in geriatric care facilities and other environments.

Determine the performance and usability of the wearable sensor system in a geriatric care facility with actual residents going about their daily lives.

Specific Aims:

  1. Determine performance of motion data collect ion system for monitoring geriatric residents as they go about their daily life in a geriatric center
  2. Determine tolerability of wearing sensors by geriatric residents
  3. Understand how medical staff interacts with monitored residents and the sensor devices
  4. Determine if the sensor system's algorithms can identify falls

Objectives:

  1. Analyze the motion data generated by the system to determine system performance. The list of performance metrics will include: (a) system up-time, (b) continuity of data collection (c) sensor device failure rate, (d) sensor device battery life (e) simultaneous collection of data when multiple monitored residents are in the same localized area.
  2. Assess the tolerability of wearing the devices over the course of a day using a survey administered to residents.
  3. Assess the usability of the sensor system using a survey administered to care givers.
  4. Compare events flagged as falls by system algorithms with the fall log produced by Garrison staff, cross-verified against personal fall logs, to determine the ability of the system to detect falls.

Study Type : Interventional  (Clinical Trial)
Estimated Enrollment : 10 participants
Intervention Model: Single Group Assignment
Masking: None (Open Label)
Primary Purpose: Prevention
Official Title: Operability and Implementation of a Patient Motion Monitoring System Using Wireless Body Worn Sensors
Study Start Date : August 2014
Estimated Primary Completion Date : July 2018
Estimated Study Completion Date : December 2018

Resource links provided by the National Library of Medicine

MedlinePlus related topics: Falls

Arm Intervention/treatment
Experimental: Wireless Body-Worn Sensors
Elderly patients will wear sensors (Smart Slippers and a belt-clip sensor) as they go about their daily life in a geriatric care center.
Device: Smart Slipper
The shoe measures foot pressure and motion allowing gait to be quantified.

Device: Belt-Clip Sensor
The sensor measures acceleration of the body allowing falls to be detected.




Primary Outcome Measures :
  1. Detection of Fall Incidences [ Time Frame: 6 months ]
    Participants will be monitored for falls. The detection of fall events as determined by the sensors will be compared to the fall log kept by Garrison Geriatric Center.



Information from the National Library of Medicine

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Ages Eligible for Study:   45 Years to 85 Years   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   Yes
Criteria

Inclusion Criteria:

  1. At least 30 day resident of Garrison.
  2. Deemed mentally competent by primary care provider to make decisions regarding their daily shoe wear.
  3. A resident prone to falls is eligible.
  4. Willing to wear shoes and offer high level of compliance to study
  5. Able to provide informed consent
  6. Able to complete survey
  7. Age range: 45-85 yrs

Exclusion Criteria:

1. Unwilling to participate 2. Not mentally competent to provide informed consent


Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT02272933


Contacts
Contact: Tim Dallas, PhD 806-834-6856 tim.dallas@ttu.edu
Contact: Ron Banister, MD 806-438-3695 ron.banister@ttuhsc.edu

Locations
United States, Texas
Garrison Geriatric Education and Care Center Recruiting
Lubbock, Texas, United States, 79415
Contact: Wendy Grimes, MSN-RN    806-763-4455    wjgrimes@sears-methodist.com   
Contact: Barbara Bratcher, MSN-RN    806-763-4455    bdbratcher@sears-methodist.com   
Sponsors and Collaborators
Texas Tech University Health Sciences Center
Texas Tech University
AT&T Research Labs
ACM
Investigators
Principal Investigator: Ron Banister, MD Texas Tech University Health Sciences Center

Responsible Party: Texas Tech University Health Sciences Center
ClinicalTrials.gov Identifier: NCT02272933     History of Changes
Other Study ID Numbers: L14-125
First Posted: October 23, 2014    Key Record Dates
Last Update Posted: June 4, 2018
Last Verified: June 2018

Additional relevant MeSH terms:
Gait Disorders, Neurologic
Neurologic Manifestations
Nervous System Diseases
Signs and Symptoms