Understanding Characteristics of User Adherence to Optimize the Use of Home Hand Rehabilitation Technology.

Home-based rehabilitation can serve as an adjunct to in-clinic rehabilitation, encouraging users to engage in more practice. However, conventional home-based rehabilitation programs suffer from low adherence and high drop-out rates. Wearable movement sensors coupled with computer games can be more engaging, but have highly variable adherence rates. Here we examined characteristics of user adherence by analyzing unsupervised, wearable grip sensor-based home-hand rehabilitation data from 1,587 users. We defined three different classes of users based on activity level: low users (<2 days), medium users (2 - 9 days), and power users (> 9 days). The probability of using the device more than two days was positively correlated with first day game success (p = 0.91, p<. 001), and number of sessions played on the first day (p = 0.87, p<. 001) but negatively correlated with parameter exploration (total number of game adjustments / total number of sessions played) on the first day (p = - 0.31, p= 0.05). Compared to low users, power users on the first day had more game success (65.18 ± 25.76 %vs. 54.94 ± 30.31 %,p <. 001), parameter exploration (25.47 ± 22.78 % vs. 12.05 ± 20.56 %, p <. 001), and game sessions played (7.60 ± 6.59 sessions vs. 4.04 ± 3.56 sessions, p <. 001). These observations support the premise that initial game success which is modulated by strategically adjusting parameters when necessary is a key determinant of adherence to rehabilitation technology.

Feasibility of home hand rehabilitation using musicglove after chronic spinal cord injury.

STUDY DESIGN: Randomized, controlled single-blind cross over study. This study was registered on ClinicalTrials.gov (NCT02473614). OBJECTIVES: Examine usership patterns and feasibility of MusicGlove for at home hand rehabilitation therapy following chronic spinal cord injury. SETTING: Homes of participants. METHODS: Ten participants with chronic spinal cord injury completed two baseline assessments of hand function. After a stable baseline was determined all participants were randomized into two groups: Experimental and Control. Each group was given a recommended therapy dosage. Following this participants switched interventions. RESULTS: On average participants had higher levels of compliance (6.1 ± 3.5 h.), and completed more grips (15,760 ± 9,590 grips) compared to participants in previous stroke studies using the same device. Participants modulated game parameters in a manner consistent with optimal challenge principles from motor learning theory. Participants in the experimental group increased their prehension ability (1 ± 1.4 MusicGlove, 0.2 ± 0.5 Control) and performance (1.4 ± 2.2 MusicGlove, 0.4 ± 0.55 Control) on the Graded and Redefined Assessment of Strength, Sensibility, and Prehension subtests. Increases in performance on the Box and Blocks Test also favored the experimental group compared to the conventional group at the end of therapy (4.2 ± 5.9, -1.0 ± 3.4 respectively). CONCLUSIONS: MusicGlove is a feasible option for hand therapy in the home-setting for individuals with chronic SCI. Participants completed nearly twice as many gripping movements compared to individuals from the sub-acute and chronic stroke populations, and a number far greater than the number of movements typically achieved during traditional rehabilitation.

Force acquisition frequency is less impaired compared to grip strength or hand dexterity in individuals with chronic stroke.

Despite numerous studies that show force regulation is impaired after stroke, two recent studies suggest that the ability to regulate submaximal, isometric grip forces may remain substantially intact. Here we asked how this aspect of hand motor control, measured for both a power grip and pinch grip, compares to two other key aspects of hand function-grip strength and dexterity. For 20 individuals with a range of hand impairment levels in the chronic phase of stroke (Age: 62 ± 16.0 years, Time post stroke: 958.3 ± 966.5 days, Sex: 19 M 1F) we quantified the average rate of target acquisition for force targets in the range of 3 to 30% maximum voluntary contraction as participants used the two different grips to squeeze a force sensor to control a cursor on a screen. The same force sensor was used to assess subject grip strength for the two grips, while dexterity was assessed using the Box and Blocks Test (BBT), and the Nine Hole Peg Test (NHPT) for both the paretic and non-paretic hand. On average, the relative rate of force acquisition of the paretic hand using a power grip was 74.0 ± 18.6 SD % of the non-paretic hand, a value significantly higher than the 48.6 ± 25.6 SD% for grip strength (paired t test, p < .005) or the 41.4 ± 29.1 SD % (p < .005) and 23.3 ± 30.1 SD % (p < .005) for the BBT and NHPT, respectively. Results were similar for the lateral pinch grip, suggesting similar thumb force tracking performance. Grip force tracking, measured as rate of force acquisition, is less impaired after stroke than hand strength or dexterity, a finding with implications for the neural mechanisms of stroke and the design of assistive technologies.

Feasibility of Wearable Sensing for In-Home Finger Rehabilitation Early After Stroke.

Wearable grip sensing shows potential for hand rehabilitation, but few studies have studied feasibility early after stroke. Here, we studied a wearable grip sensor integrated with a musical computer game (MusicGlove). Among the stroke patients admitted to a hospital without limiting complications, 13% had adequate hand function for system use. Eleven subjects used MusicGlove at home over three weeks with a goal of nine hours of use. On average they achieved 4.1 ± 3.2 (SD) hours of use and completed 8627 ± 7500 grips, an amount comparable to users in the chronic phase of stroke measured in a previous study. The rank-order usage data were well fit by distributions that arise in machine failure theory. Users operated the game at high success levels, achieving note-hitting success >75% for 84% of the 1061 songs played. They changed game parameters infrequently (31% of songs), but in a way that logically modulated challenge, consistent with the Challenge Point Hypothesis from motor learning. Thus, a therapy based on wearable grip sensing was feasible for home rehabilitation, but only for a fraction of subacute stroke subjects. Subjects made usage decisions consistent with theoretical models of machine failure and motor learning.