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  • Optimizing the Use of Mobile Wireless Activity Sensors to Assess Postoperative Functional Recovery

    Final Number:
    1192

    Authors:
    Blake Eaton Samuel Taylor BA; Brett Youngerman MD; Randy D'Amico MD; Geoffrey Appelboom MD; Eliza M Bruce BA; Christopher Eliot Mandigo MD

    Study Design:
    Other

    Subject Category:

    Meeting: Congress of Neurological Surgeons 2014 Annual Meeting

    Introduction: Mobile wireless sensors have the potential to provide objective, real-time clinical data relevant to management of a variety of diseases. One recent focus is the role of fitness activity tracking devices in measuring functional recovery. In the absence of standardized methods to use or interpret data from these devices, their clinical use has been limited. We present a single case comparing the data from wireless activity trackers to the clinical assessment of functional recovery in an effort to optimize use of this technology.

    Methods: An 84 year-old woman with right-sided weakness and hyperreflexia underwent C3-C7 laminoplasty for cervical spondylotic myelopathy. Activity trackers (FitBits TM) were placed simultaneously at four locations on the patient postoperatively: one on each side of a waist belt and one above each ankle. The patient received routine postoperative care. Data from the devices was compared to assessment by physical therapists, neurological exam, and independent observation.

    Results: Postoperatively, the patient improved clinically with stable residual deficits noted in the right lower extremity. On postoperative day 3, devices were applied and the patient received routine physical therapy for 25 minutes. The patient ambulated 150 feet (178 steps reported by 2 independent observers), Right and left ankle devices reported 163 (8.5% underreporting) and 230 steps (29% overreporting), respectively. The devices on the waist recorded minimal steps. During the physical therapy session, she was noted to have decreased weight shift and swing phase of gait in the left lower extremity potentially explaining the differences recorded by the device.

    Conclusions: There may be variability in the reported metrics of activity trackers based on specific placement. In particular, placement on extremities with impaired function may result in underreporting of data. Accurate objective reporting requires optimized placement of activity trackers, particularly in the evaluation of functional recovery.

    Patient Care: This case highlights a potential explanation for the currently limited clinical use of activity sensors, particularly in patients with neurological injury. In the future, finding an optimized protocol for use of these devices in measuring functional recovery will allow improved patient care by providing more data on outcomes than traditional assessments such as duration of hospital stay.

    Learning Objectives: By the conclusion of this session, participants should be able to 1) Describe the importance of assessing functional recovery, and the importance of coming up with standardized methods of using activity sensors to provide objective measures of this recovery 2) Discuss, in small groups, the potential problems with variability in data measurement and interpretation when using the devices, and what the solutions might be 3) Identify an effective treatment in the future that would utilize data from activity sensors.

    References: Gurol-Urganci I, de Jongh T, Vodopivec-Jamsek V, Car J, Atun R (2008) Mobile phone messaging for communicating results of medical investigations. Cochrane Database of Systematic Reviews doi: 10.1080/01972240802019970 Bastawrous A, Armstrong MJ. Mobile health use in low- and high-income countries: an overview of the peer-reviewed literature. J R Soc Med 2013;106:130–42. K.L. Bussey-Smith, R.D. Rossen. A systematic review of randomized control trials evaluating the effectiveness of interactive computerized asthma patient education programs Ann. Allergy Asthma Immunol., 98 (June (6)) (2007), pp. 507–516 quiz 16, 66 A Qualitative Analysis of User Experiences With a Self-Tracker for Activity, Sleep, and Diet. Jeongeun Kim. Interact J Med Res 2014 (Mar 04); 3(1):e8.

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