Manual physical balance assistance of therapists during gait training of stroke survivors: characteristics and predicting the timing

Journal of NeuroEngineering and Rehabilitation, Dec 2017

During gait training, physical therapists continuously supervise stroke survivors and provide physical support to their pelvis when they judge that the patient is unable to keep his balance. This paper is the first in providing quantitative data about the corrective forces that therapists use during gait training. It is assumed that changes in the acceleration of a patient’s COM are a good predictor for therapeutic balance assistance during the training sessions Therefore, this paper provides a method that predicts the timing of therapeutic balance assistance, based on acceleration data of the sacrum. Eight sub-acute stroke survivors and seven therapists were included in this study. Patients were asked to perform straight line walking as well as slalom walking in a conventional training setting. Acceleration of the sacrum was captured by an Inertial Magnetic Measurement Unit. Balance-assisting corrective forces applied by the therapist were collected from two force sensors positioned on both sides of the patient’s hips. Measures to characterize the therapeutic balance assistance were the amount of force, duration, impulse and the anatomical plane in which the assistance took place. Based on the acceleration data of the sacrum, an algorithm was developed to predict therapeutic balance assistance. To validate the developed algorithm, the predicted events of balance assistance by the algorithm were compared with the actual provided therapeutic assistance. The algorithm was able to predict the actual therapeutic assistance with a Positive Predictive Value of 87% and a True Positive Rate of 81%. Assistance mainly took place over the medio-lateral axis and corrective forces of about 2% of the patient’s body weight (15.9 N (11), median (IQR)) were provided by therapists in this plane. Median duration of balance assistance was 1.1 s (0.6) (median (IQR)) and median impulse was 9.4Ns (8.2) (median (IQR)). Although therapists were specifically instructed to aim for the force sensors on the iliac crest, a different contact location was reported in 22% of the corrections. This paper presents insights into the behavior of therapists regarding their manual physical assistance during gait training. A quantitative dataset was presented, representing therapeutic balance-assisting force characteristics. Furthermore, an algorithm was developed that predicts events at which therapeutic balance assistance was provided. Prediction scores remain high when different therapists and patients were analyzed with the same algorithm settings. Both the quantitative dataset and the developed algorithm can serve as technical input in the development of (robot-controlled) balance supportive devices.

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Manual physical balance assistance of therapists during gait training of stroke survivors: characteristics and predicting the timing

Haarman et al. Journal of NeuroEngineering and Rehabilitation Manual physical balance assistance of therapists during gait training of stroke survivors: characteristics and predicting the timing Juliet A. M. Haarman 0 1 2 Erik Maartens 0 1 Herman van der Kooij 0 Jaap H. Buurke 0 1 Jasper Reenalda 0 1 Johan S. Rietman 0 1 0 Department of Biomechanical Engineering, University of Twente , Drienerlolaan 5, 7522 NB Enschede , the Netherlands 1 Roessingh Research and Development , Roessinghsbleekweg 33b, 7522 AH Enschede , the Netherlands 2 Roessingh Research and Development , Roessinghsbleekweg 33b, PO Box 310, 7500 AH Enschede , the Netherlands Background: During gait training, physical therapists continuously supervise stroke survivors and provide physical support to their pelvis when they judge that the patient is unable to keep his balance. This paper is the first in providing quantitative data about the corrective forces that therapists use during gait training. It is assumed that changes in the acceleration of a patient's COM are a good predictor for therapeutic balance assistance during the training sessions Therefore, this paper provides a method that predicts the timing of therapeutic balance assistance, based on acceleration data of the sacrum. Methods: Eight sub-acute stroke survivors and seven therapists were included in this study. Patients were asked to perform straight line walking as well as slalom walking in a conventional training setting. Acceleration of the sacrum was captured by an Inertial Magnetic Measurement Unit. Balance-assisting corrective forces applied by the therapist were collected from two force sensors positioned on both sides of the patient's hips. Measures to characterize the therapeutic balance assistance were the amount of force, duration, impulse and the anatomical plane in which the assistance took place. Based on the acceleration data of the sacrum, an algorithm was developed to predict therapeutic balance assistance. To validate the developed algorithm, the predicted events of balance assistance by the algorithm were compared with the actual provided therapeutic assistance. Results: The algorithm was able to predict the actual therapeutic assistance with a Positive Predictive Value of 87% and a True Positive Rate of 81%. Assistance mainly took place over the medio-lateral axis and corrective forces of about 2% of the patient's body weight (15.9 N (11), median (IQR)) were provided by therapists in this plane. Median duration of balance assistance was 1.1 s (0.6) (median (IQR)) and median impulse was 9.4Ns (8.2) (median (IQR)). Although therapists were specifically instructed to aim for the force sensors on the iliac crest, a different contact location was reported in 22% of the corrections. (Continued on next page) - (Continued from previous page) Conclusions: This paper presents insights into the behavior of therapists regarding their manual physical assistance during gait training. A quantitative dataset was presented, representing therapeutic balance-assisting force characteristics. Furthermore, an algorithm was developed that predicts events at which therapeutic balance assistance was provided. Prediction scores remain high when different therapists and patients were analyzed with the same algorithm settings. Both the quantitative dataset and the developed algorithm can serve as technical input in the development of (robotcontrolled) balance supportive devices. Background Stroke survivors with a Functional Ambulation Category (FAC) of 3 often experience reduced balance control and difficulties with independent ambulation [ 1 ]. Physical therapists focus on improving these aspects in rehabilitation therapy, for instance by training tasks that specifically relate to Activities of Daily Living (ADL’s) such as overground walking in and around the house [ 2, 3 ]. During these training sessions, therapists continuously need to supervise patients when they walk. When patients lose their balance, therapists provide manual physical balance assistance to the body in the form of small corrective forces. In any given situation, therapists consider patient-specific examination findings to determine if and when balance assistance is needed, such as a patient’s specific muscle strength, isolated movement capacity, reaction or movement time deficits, co-morbid sensory loss, coordination deficits, as well as, fatigue status and fall history. Providing balance assistance not only allows patients to continue their training safely, it also lets them experience the boundaries of their abilities without actually falling. Such a process of experiencing trial-anderror in (re)learning motor tasks is commonly referred to as error-based training, a concept often applied in stroke rehabilitation [4]. The applicability of this concept was confirmed in observations during training sessions by the authors and by personal communication with therapists, who state that an optimal tradeoff be (...truncated)


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Juliet A. M. Haarman, Erik Maartens, Herman van der Kooij, Jaap H. Buurke, Jasper Reenalda, Johan S. Rietman. Manual physical balance assistance of therapists during gait training of stroke survivors: characteristics and predicting the timing, Journal of NeuroEngineering and Rehabilitation, pp. 125,