Journal of NeuroEngineering and Rehabilitation - Latest Comments

Are smartphones a smart way to go?

Jeffrey Hausdorff — 2012-02-20T11:56:46Z

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.

References:

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.

An interesting and important contribution to gait retraining after stroke

Alberto Esquenazi — 2012-02-13T15:13:32Z

The study is retrospective and has some methodological weakness but even with this the authors bring forward a proposal for an innovative therapeutic approach namely "Body Weight Supported Robotic Gait Training" that is of value particularly in the early phase of rehabilitation when patients are limited by their capacity to participate in high intensity, high repetition walking as a therapeutic intervention.

The authors did not mention that there may be different mechanisms involved in the intervention they generically termed as "Body Weight Supported Robotic Gait Training". Several of this devices are now available and two primary approaches to this technology exist.
1. End Effector devices as the one used in this study which do not constrained hip and knee joint motion allowing some variability in the kinematic pattern during walking and
2. Robotic guided movement which consists of an exoskeleton that independently controls in an active manner each hip and knee position during walking and provides passive control at the ankles.
The approaches for each one of these two methods of intervention are not the same and not clearly understood or differentiated in the literature.

Their work is an encouragement for others to further evaluate these new technologies and to look in a more scientific manner how to select the appropriate patient population as well as the timing, dosing and intensity of the intervention that will best serve the patients we care for.

Comment on Belda-Lois et al.

william rymer — 2012-01-23T10:28:36Z

This review focuses on assessing the impact of a wide range of rehabilitation therapies promoting gait recovery after hemispheric stroke. The review emphasizes the role of reorganizing the central nervous system in promoting gait recovery, by contrasting this approach with classical therapies targeting peripheral neuromuscular interventions. The review is detailed, broad and comprehensive.

The authors affirm the position taken recently by an number of United States Agencies including the Veterans Administration, the Department of Defense (1) and the American Heart Association (2), that gait retraining with either body weight supported treadmill training techniques, or with robotic devices has not been shown to be demonstrably superior to traditional therapy methods.

It is interesting to speculate as to why so many therapies appear to be promising in preliminary studies, yet fail to reach satisfactory outcomes in larger multicenter clinical trials. There are several possibilities:

1. Difficulties in standardizing therapy in Multicenter trials
In many recent clinical trials, studies were performed in multiple sites, and relied on multiple therapists for patient selection and care delivery. It is rather hard to be certain that in such multicenter trials, different sites adopt consistent study entry criteria and that they administer therapy in a consistent manner.

2. Outcome Assessments
Our outcome assessments for gait retraining are relatively imprecise. Most investigators rely on a 10-meter walk, which is a measure of speed, and a 6 min. walk, which is a measure of endurance. There is rarely an opportunity for assessment of gait kinematics or even gait asymmetry.

3. Timing of therapy
Many researchers believe that there may be a window of opportunity arising relatively early after a stroke, conceivably beginning within a few days of the acute lesion. This time frame is not usually regarded as either safe or appropriate for energetic early gait retraining, but this interval may be our best chance to modify cortical structure and function.

For all these reasons, we may be missing promising therapeutic responses, and treating potentially rational therapies as ineffectual.

Finally, the authors of this review assert that combination therapies appear to be the most effective. While this claim may well be correct, a rational experimental analysis of combination therapies is very difficult because of the need to use many different dose combinations in order to precisely chracterize combinatorial effects.

For the future, this reviewer would prefer to see a more rigorous experimental analysis of individual therapies before launching into studies requiring that multiple therapies be delivered.

Key References:

1. Management of Stroke Rehabilitation Working Group. Management of stroke rehabilitation. VA/DOD Clinical Practice Guideline. VA/DOD Evidence Based Practice. Version 2.0, 2010. Washington, DC: Veterans Health Administration, Department of Defense; 2010. Available at: http://www.healthquality.va.gov/stroke/stroke_full_221.pdf.

2. Comprehensive Overview of Nursing and Interdisciplinary Rehabilitation Care of the Stroke Patient : A Scientific Statement From the American Heart Association Elaine L. Miller, Laura Murray, Lorie Richards, Richard D. Zorowitz, Tamilyn Bakas, Patricia Clark and Sandra A. Billinger Stroke 2010, 41:2402-2448: originally published online September 2, 2010

Reassessing standardised outcome measures

Caoimhe Bennis — 2011-11-30T16:35:10Z

It is of utmost importance that we reassess the standard in clinical outcome measures. Many of the scales used in the clinical setting are considered by therapists to be outdated, unreliable and time consuming.
Therefore, many of the findings in standard measures utilised in research are unable to be reproduced in the clinical setting.

This study looks to assess the reliability of the modified PASS or SwePASS in which clarifications of the manual have been made. The results seem positive but it is important to note other efficacy factors which were discussed such as time to complete test and ways to reduce the floor and ceiling effect.

As mentioned, it would be important to look further at interrater reliability but this is a good start to the difficult task of updating clinical outcome measures.