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  1. Are smartphones a smart way to go?

    Jeffrey Hausdorff, Tel-Aviv Sourasky Medical Center, Tel-Aviv University, Harvard Medical School

    20 February 2012

    Technology that enables clinicians and researchers to quantify and treat balance and gait problems is rapidly evolving. For a long time, laboratory-based, specialized equipment that included multiple cameras and embedded force platforms were the heart and soul of the analysis of gait and balance. Many treatments were also centered around these powerful technologies. Over the past two decades or so, much effort has been invested into the use of wearable computers, also commonly referred to as body-fixed sensors. Advantages of an approach based on body-fixed sensors include cost and space, and the possibility of bringing the measurement system to the patient and clinic rather than the other way around. An additional key advantage is the potential for long-term recordings that may more closely reflect everyday abilities, their dynamics and changes over time and that may be less prone to "white coat" syndromes [1,2].

    More recently, a number of studies have explored the use of body-fixed sensors as the basis of therapeutic interventions [3,4]. Here too, issues of cost and accessibility play an important role. A traditional approach requires a patient to make her way to an outpatient clinic several times a week. However, with body-fixed sensors, therapy can be performed in the home, potentially enhancing compliance and the frequency and duration of treatment, thereby augmenting the therapeutic benefits, while lowering costs, travel time, and therapist time.

    The pilot study by B.C. Lee et al. (JNER, 2012) nicely illustrates this type of approach while taking advantage of even more recent advantages in technology: the smartphone. Many of today's smartphones incorporate inertial sensors, processing power, memory and other features that are needed to train balance and gait using body-fixed sensors [5,6]. In their intriguing pilot study, Lee et al. use a smartphone and a low-cost vibro-tactile sensor to provide feedback that is designed to enhance postural control. The initial results with this system are quite promising. With minimal extra cost, the smartphone technology helped controls and patients with vestibular impairment to markedly improve their postural control. While the number of subjects is quite small and many questions about efficacy and retention remain to be determined, the approach nicely demonstrates the potential of the smartphone. More work is needed for this line of research, however, these initial findings are promising and consistent with other pilot studies [5,6].

    Is there a place for more expensive, dedicated equipment for quantifying gait and balance and as a therapeutic tool? Of course. Nonetheless, in an era when the population is aging and funds available for rehabilitation and research are declining, an approach that takes maximal advantage of existing, ubiquitous, low-cost technologies like the smartphone seems like a smart way to go. At least until the next generation of technology comes along.


    1. Hausdorff JM: Gait dynamics in Parkinson's disease: common and distinct behavior among stride length, gait variability, and fractal-like scaling. Chaos 2009, 19: 026113.
    2. Weiss A, Sharifi S, Plotnik M, van Vugt JP, Giladi N, Hausdorff JM: Toward automated, at-home assessment of mobility among patients with Parkinson disease, using a body-worn accelerometer. Neurorehabil Neural Repair 2011, 25: 810-818.
    3. Chiari L: Wearable systems with minimal set-up for monitoring and training of balance and mobility. Conf Proc IEEE Eng Med Biol Soc 2011, 2011: 5828-5832.
    4. Mirelman A, Herman T, Nicolai S, Zijlstra A, Zijlstra W, Becker C, Chiari L, Hausdorff JM: Audio-biofeedback training for posture and balance in patients with Parkinson's disease. J Neuroeng Rehabil 2011, 8: 35.
    5. Palmerini L, Mellone S, Rocchi L, Chiari L: Dimensionality reduction for the quantitative evaluation of a smartphone-based Timed Up and Go test. Conf Proc IEEE Eng Med Biol Soc 2011, 2011: 7179-7182.
    6. Yamada M, Aoyama T, Mori S, Nishiguchi S, Okamoto K, Ito T, Muto S, Ishihara T, Yoshitomi H, Ito H: Objective assessment of abnormal gait in patients with rheumatoid arthritis using a smartphone. Rheumatol Int 2011.

    Competing interests

    The author is a participant in two projects funded by the European Union - Seventh Framework Programme (FP7/2007-2013, CuPiD project #288516 and WIISEL project # 288878) that are, among other things, developing smartphone-based approaches for quantifying gait and detecting and treating freezing of gait.