Evaluation of Usefulness of the Elinor Console for Home-Based Stroke Rehabilitation

Backlund, Per; Taylor, Anna-Sofia Alklind; Engström, Henrik; Johannesson, Mikael; Lebram, Mikael; Slijper, Angelique; Svensson, Karin; Poucette, Jesper; Sunnerhagen, Katharina Stibrant

doi:10.1109/vs-games.2011.20

Cited by 9 publications

(6 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The included articles were published between 2004 and 2017. They represented 25 projects: 14 [22][23][24][25][26][27][28][29][30][31][32][33][34][35][36] conducted in the United States, 12 [37][38][39][40][41][42][43][44][45][46][47][48][49][50][51][52][53] in Europe (including the United Kingdom, Sweden, Italy, Switzerland, the Netherland), 1 54 in New Zealand, and 1 55 in China. The following types of technologies emerge in the articles: games (14 projects), telerehabilitation (8 projects), robotic devices (7 projects), virtual reality (6 projects), wearable sensors (4 projects), and tablets (2 projects).…”

Section: General Overviewmentioning

confidence: 99%

“…Overall, the quantitative and qualitative findings of the studies show that home-based technologies offered unique opportunities and benefits to deliver rehabilitation to patients at home. First, some studies found that users had improved motor skills after the intervention 24,[27][28][29][30][33][34][35][37][38][39][40]46,48,53,54 and that home-based rehabilitation technologies offer equivalent quality as conventional therapies 55 . In the 12-week study by Chen et al 55 , both the home based telerehabilitation and conventional rehabilitation groups demonstrated significant effects within groups with three time points in increasing Modified Barthel Index, Berg Balance Scale.…”

Section: Study Findingsmentioning

confidence: 99%

See 1 more Smart Citation

Home-based technologies for stroke rehabilitation: A systematic review

Chen

Abel

Janecek

et al. 2019

International Journal of Medical Informatics

210

156

View full text Add to dashboard Cite

Background-Many forms of home-based technology targeting stroke rehabilitation have been devised, and a number of human factors are important to their application, suggesting the need to examine this information in a comprehensive review. Objective-The systematic review aims to synthesize the current knowledge of technologies and human factors in home-based technologies for stroke rehabilitation. Methods-We conducted a systematic literature search in three electronic databases (IEEE, ACM, PubMed), including secondary citations from the literature search. We included articles that used technological means to help stroke patients conduct rehabilitation at home, reported empirical studies that evaluated the technologies with patients in the home environment, and were published in English. Three authors independently conducted the content analysis of searched articles using a list of interactively defined factors. Results-The search yielded 832 potentially relevant articles, leading to 31 articles that were included for in-depth analysis. The types of technology of reviewed articles included games, telerehabilitation, robotic devices, virtual reality devices, sensors, and tablets. We present the merits and limitations of each type of technology. We then derive two main human factors in designing home-based technologies for stroke rehabilitation: designing for engagement (including external and internal motivation) and designing for the home environment (including understanding the social context, practical challenges, and technical proficiency).

show abstract

Section: General Overviewmentioning

confidence: 99%

Section: Study Findingsmentioning

confidence: 99%

Home-based technologies for stroke rehabilitation: A systematic review

Chen

Abel

Janecek

et al. 2019

International Journal of Medical Informatics

210

156

View full text Add to dashboard Cite

show abstract

“…A benefit is if it can be used in the home environment. The experiences from a pilot study using computer game-based training in home environment suggested that it could be an alternative [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

Computer game-based upper extremity training in the home environment in stroke persons: a single subject design

Slijper

Svensson

Backlund

et al. 2014

J NeuroEngineering Rehabil

Self Cite

View full text Add to dashboard Cite

BackgroundThe objective of the present study was to assess whether computer game-based training in the home setting in the late phase after stroke could improve upper extremity motor function.MethodsTwelve subjects with prior stroke were recruited; 11 completed the study.DesignThe study had a single subject design; there was a baseline test (A1), a during intervention test (B) once a week, a post-test (A2) measured directly after the treatment phase, plus a follow-up (C) 16–18 weeks after the treatment phase. Information on motor function (Fugl-Meyer), grip force (GrippitR) and arm function in activity (ARAT, ABILHAND) was gathered at A1, A2 and C. During B, only Fugl-Meyer and ARAT were measured. The intervention comprised five weeks of game-based computer training in the home environment. All games were designed to be controlled by either the affected arm alone or by both arms. Conventional formulae were used to calculate the mean, median and standard deviations. Wilcoxon’s signed rank test was used for tests of dependent samples. Continuous data were analyzed by methods for repeated measures and ordinal data were analyzed by methods for ordered multinomial data using cumulative logistic models. A p-value of < 0.05 was considered statistically significant.ResultsSix females and five males, participated in the study with an average age of 58 years (range 26–66). FMA-UE A-D (motor function), ARAT, the maximal grip force and the mean grip force on the affected side show significant improvements at post-test and follow-up compared to baseline. No significant correlation was found between the amount of game time and changes in the outcomes investigated in this study.ConclusionThe results indicate that computer game-based training could be a promising approach to improve upper extremity function in the late phase after stroke, since in this study, changes were achieved in motor function and activity capacity.

show abstract

“…This innovative motion-based way of interacting with games has opened the doors to not only using these technologies for games but also for clinical use such as physical therapy and exercise. Several researchers have already grasped this opportunity and have built exercise games/exergames [1] [2] and physiotherapy games [3] [4]. Some work have also been carried out in using motion-based gaming devices for detecting and analyzing tremors using the Nintendo Wii [5] [6].…”

Section: Introductionmentioning

confidence: 99%

Using the Kinect for detecting tremors: Challenges and opportunities

Sooklal

Mohan

Teelucksingh

2014

IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)

View full text Add to dashboard Cite

The Kinect sensor is an attachment for the Xbox gaming console which allows players to interact with games through body movement. This paper explores the possibility of using the Kinect in a clinical setting for detection of Parkinson's, postural, flapping, titubation and voice tremors. All of the physical tremors were simulated and the ability of the Kinect to capture them was evaluated. The Kinect was also used to record voice data from real voice tremors patients. Physical and voice data were gathered from healthy persons for comparison. The results showed that the Kinect could reliably detect voice, postural and Parkinson's tremors. A very consistent graph could be obtained repeatedly for both Parkinson's and postural tremors. For voice tremors there was also a consistent pattern that differentiated a normal voice from one with a tremor. We have therefore proven that the Kinect can consistently record Parkinson's, postural and voice tremors.

show abstract

Evaluation of Usefulness of the Elinor Console for Home-Based Stroke Rehabilitation

Cited by 9 publications

References 15 publications

Home-based technologies for stroke rehabilitation: A systematic review

Home-based technologies for stroke rehabilitation: A systematic review

Computer game-based upper extremity training in the home environment in stroke persons: a single subject design

Using the Kinect for detecting tremors: Challenges and opportunities

Contact Info

Product

Resources

About