George D. Fulk

Monitoring of Posture Allocations and Activities by a Shoe-Based Wearable Sensor

Monitoring of posture allocations and activities enables accurate estimation of energy expenditure and may aid in obesity prevention and treatment. At present, accurate devices rely on multiple sensors distributed on the body and thus may be too obtrusive for everyday use. This paper presents a novel wearable sensor, which is capable of very accurate recognition of common postures and activities. The patterns of heel acceleration and plantar pressure uniquely characterize postures and typical activities while requiring minimal preprocessing and no feature extraction. The shoe sensor was tested in nine adults performing sitting and standing postures and while walking, running, stair ascent/descent and cycling. Support vector machines (SVMs) were used for classification. A fourfold validation of a six-class subject-independent group model showed 95.2% average accuracy of posture/activity classification on full sensor set and over 98% on optimized sensor set. Using a combination of acceleration/pressure also enabled a pronounced reduction of the sampling frequency (25 to 1 Hz) with out significant loss of accuracy (98% versus 93%). Subjects had shoe sizes (US) M9.5-11 and W7-9 and body mass index from 18.1 to 39.4 kg/m2 and thus suggesting that the device can be used by individuals with varying anthropometric characteristics.

Test-retest reliability and minimal detectable change of gait speed in individuals undergoing rehabilitation after stroke.

Background and Purpose: Gait speed is commonly used to assess walking ability in persons with stroke. Previous research related to the psychometric properties of gait speed has been conducted primarily with individuals who were able to walk independently and/or were in the later stages of recovery after stroke. The purpose of this research was to examine the test-retest reliability and minimal detectable change (MDC90) of gait speed in individuals with stroke who required varying levels of assistance to ambulate during rehabilitation. Methods: Patients who could ambulate with or without physical assistance and were undergoing inpatient rehabilitation were recruited. Gait speed was measured over the middle five meters of a nine-meter walk at a comfortable pace. Data were analyzed using the intraclass correlation coefficient (ICC2,1) and the MDC90. Results: Thirty-five patients who were a mean 34.5 (standard deviation = 17.7) days post-stroke agreed to participate. For all the subjects combined, the ICC2,1 was 0.862 and MDC90 was 0.30 m/sec. For the 13 subjects who required physical assistance to walk, the ICC2,1 = 0.971 and MDC90 = 0.07 m/sec. For the 22 subjects who could walk without physical assistance, the ICC2,1 = 0.80 and MDC90 = 0.36 m/sec. Discussion: Gait speed is a reliable measure of walking ability for a wide variety of patients undergoing rehabilitation after stroke. Gait speed is more sensitive to change in patients who require physical assistance to walk than in those who can walk without assistance. A change of more than 0.30 m/sec may be necessary in order to determine whether a change in gait speed exceeds measurement error and patient variability.

Clinometric properties of the six-minute walk test in individuals undergoing rehabilitation poststroke

The 6-minute walk test (6MWT) is commonly used to measure walking ability. The purpose of this study was to determine the test-retest reliability and concurrent and construct validity of the 6MWT in patients who were actively undergoing inpatient rehabilitation poststroke. Thirty-seven patients undergoing inpatient rehabilitation after a stroke participated; mean age was 66.3 years and mean time since stroke was 33.7 days. Patients underwent two 6MWT trials with 1–3 days between trials. Additional outcome measures taken were gait speed and the Functional Independence MeasureTM (FIMTM). The 6MWT exhibited high test-retest reliability; ICC2,1 0.973 (95% CI=0.925–0.988) and a minimal detectable change (MDC90) of 54.1 m. The 6MWT was strongly to moderately correlated with gait speed (r=0.89), locomotion (walk) FIMTM (r=0.69), and motor FIMTM (r=0.52). The 6MWT is a clinically useful measure of walking ability poststroke. It is reliable and is related to other measures of walking ability and function that are commonly used during rehabilitation after stroke.

Accuracy of 2 Activity Monitors in Detecting Steps in People With Stroke and Traumatic Brain Injury

Background Advances in sensor technologies and signal processing techniques provide a method to accurately measure walking activity in the home and community. Activity monitors geared toward consumer or patient use may be an alternative to more expensive monitors designed for research to measure stepping activity. Objective The objective of this study was to examine the accuracy of 2 consumer/patient activity monitors, the Fitbit Ultra and the Nike+ Fuelband, in identifying stepping activity in people with stroke and traumatic brain injury (TBI). Secondarily, the study sought to compare the accuracy of these 2 activity monitors with that of the StepWatch Activity Monitor (SAM) and a pedometer, the Yamax Digi-Walker SW-701 pedometer (YDWP). Design A cross-sectional design was used for this study. Method People with chronic stroke and TBI wore the 4 activity monitors while they performed the Two-Minute Walk Test (2MWT), during which they were videotaped. Activity monitor estimated steps taken were compared with actual steps taken counted from videotape. Accuracy and agreement between activity monitor estimated steps and actual steps were examined using intraclass correlation coefficients (ICC [2,1]) and the Bland-Altman method. Results The SAM demonstrated the greatest accuracy (ICC [2,1]=.97, mean difference between actual steps and SAM estimated steps=4.7 steps) followed by the Fitbit Ultra (ICC [2,1]=.73, mean difference between actual steps and Fitbit Ultra estimated steps=−9.7 steps), the YDWP (ICC [2,1]=.42, mean difference between actual steps and YDWP estimated steps=−28.8 steps), and the Nike+ Fuelband (ICC [2,1]=.20, mean difference between actual steps and Nike+ Fuelband estimated steps=−66.2 steps). Limitations Walking activity was measured over a short distance in a closed environment, and participants were high functioning ambulators, with a mean gait speed of 0.93 m/s. Conclusions The Fitbit Ultra may be a low-cost alternative to measure the stepping activity in level, predictable environments of people with stroke and TBI who can walk at speeds ≥0.58 m/s.

Predicting Home and Community Walking Activity in People With Stroke

OBJECTIVE To determine the ability of the 6-minute walk test (6MWT) and other commonly used clinical outcome measures to predict home and community walking activity in high-functioning people with stroke. DESIGN Cross-sectional. SETTING Outpatient physical therapy clinic. PARTICIPANTS Participants (N=32) with chronic stroke (n=19; >6mo poststroke) with self-selected gait speed (GS) faster than .40m/s and age-matched healthy participants (n=13). INTERVENTIONS Not applicable. MAIN OUTCOME MEASURES INDEPENDENT VARIABLES 6MWT, self-selected GS, Berg Balance Scale (BBS), lower extremity motor section of the Fugl-Meyer Assessment, and Stroke Impact Scale. Dependent variable: average steps taken per day during a 7-day period, measured using an accelerometer. RESULTS 6MWT, self-selected GS, and BBS were moderately related to home and community walking activity. The 6MWT was the only predictor of average steps taken per day; it explained 46% of the variance in steps per day. CONCLUSIONS The 6MWT is a useful outcome measure in higher functioning people with stroke to guide intervention and assess community walking activity.

Automatic Detection of Temporal Gait Parameters in Poststroke Individuals

Approximately one-third of people who recover from a stroke require some form of assistance to walk. Repetitive task-oriented rehabilitation interventions have been shown to improve motor control and function in people with stroke. Our long-term goal is to design and test an intensive task-oriented intervention that will utilize the two primary components of constrained-induced movement therapy: massed, task-oriented training and behavioral methods to increase use of the affected limb in the real world. The technological component of the intervention is based on a wearable footwear-based sensor system that monitors relative activity levels, functional utilization, and gait parameters of affected and unaffected lower extremities. The purpose of this study is to describe a methodology to automatically identify temporal gait parameters of poststroke individuals to be used in assessment of functional utilization of the affected lower extremity as a part of behavior enhancing feedback. An algorithm accounting for intersubject variability is capable of achieving estimation error in the range of 2.6-18.6% producing comparable results for healthy and poststroke subjects. The proposed methodology is based on inexpensive and user-friendly technology that will enable research and clinical applications for rehabilitation of people who have experienced a stroke.

Estimating clinically important change in gait speed in people with stroke undergoing outpatient rehabilitation.

Background and Purpose: Gait speed is commonly used to assess walking ability in people with stroke. It is not clear how much change in gait speed reflects an important change in walking ability. The purpose of this study was to estimate clinically important changes in gait speed by using 2 different anchors for what is considered “important”: stroke survivors and physical therapists perceptions of change in walking ability. Methods: Participants underwent outpatient physical therapy (mean 56 days post-stroke) after a first-time stroke. Self-selected gait speed was measured at admission and discharge. At discharge, participants and their physical therapists rated their perceived change in walking ability on a 15-point ordinal Global Rating of Change (GROC) scale. Estimated important change values for gait speed were calculated by using receiver operating characteristics curves, with the participants and physical therapists GROC as the anchors. Results: The mean (SD) initial gait speed of all participants was 0.56 (0.22) m/s. The estimated important change in gait speed ranged from 0.175 m/s (participants perceived change in walking ability) to 0.190 m/s (physical therapists perceived change in walking ability), depending on the anchor. Discussion and Conclusions: During the subacute stage of recovery, individuals poststroke who experience improvements in gait speed of 0.175 m/s or greater are likely to exhibit a meaningful improvement in walking ability. The estimated clinically important change value of 0.175 m/s can be used by clinicians to set goals and interpret change in individual patients and by researchers to compare important change between groups.

Using sensors to measure activity in people with stroke.

Abstract Purpose: The purpose of this study was to determine the ability of a novel shoe-based sensor that uses accelerometers, pressure sensors, and pattern recognition with a support vector machine (SVM) to accurately identify sitting, standing, and walking postures in people with stroke. Methods: Subjects with stroke wore the shoe-based sensor while randomly assuming 3 main postures: sitting, standing, and walking. A SVM classifier was used to train and validate the data to develop individual and group models, which were tested for accuracy, recall, and precision. Results: Eight subjects participated. Both individual and group models were able to accurately identify the different postures (99.1% to 100% individual models and 76.9% to 100% group models). Recall and precision were also high for both individual (0.99 to 1.00) and group (0.82 to 0.99) models. Conclusions: The unique combination of accelerometer and pressure sensors built into the shoe was able to accurately identify postures. This shoe sensor could be used to provide accurate information on community performance of activities in people with stroke as well as provide behavioral enhancing feedback as part of a telerehabilitation intervention.

Stair Ascent With a Powered Transfemoral Prosthesis Under Direct Myoelectric Control

This paper presents experimental results of a myoelectric controller designed for reciprocal stair ascent using a transfemoral prosthesis with an actively powered knee joint. The control architecture is derived from able-bodied gait data and estimates knee torque with a linear two-state (stance/swing) impedance control form that includes proportional myoelectric torque control combined with a state-determined knee impedance. The experimentally implemented control interface affords the amputee subject with direct control of knee torque using surface electromyogram (EMG) measurements of muscles in the residual thigh supplemented with a nominal knee impedance whose set-point switches based on the detection of ground contact at the foot. Preliminary clinical evaluations of the EMG-based control system with a single subject with unilateral transfemoral amputation show robust and repeatable performance for alternating stair ascent. The amputee subject effectively modulates power output at the knee using EMG commands during stance, while leveraging the knees nominal swing-phase impedance and only modest EMG influence to achieve the desired knee trajectories during swing.

Outcome measures in neurological physical therapy practice: part I. Making sound decisions.

Standardized outcome measures (OMs) are a vital part of evidence-based practice. Despite the recognition of the importance of OMs, recent evidence suggests that the use of OMs in clinical practice is limited. Selecting the most appropriate OM enhances clinical practice by (1) identifying and quantifying body function and structure limitations; (2) formulating the evaluation, diagnosis, and prognosis; (3) informing the plan of care; and (4) helping to evaluate the success of physical therapy interventions. This article (Part I) is the first of a 2-part series on the process of selecting OMs in neurological clinical practice. We introduce a decision-making framework to guide the selection of OMs and discuss 6 main factors—what to measure, the purpose of the measure, the type of measure, patient and clinic factors, psychometric factors, and feasibility—that should be considered when selecting OMs for clinical use. The framework will then be applied to a patient case in Part II of the series (see the article “Outcome Measures in Neurological Physical Therapy Practice: Part II. A Patient-Centered Process” in this issue).