Posts Tagged telerehabilitation

[ARTICLE] Development and Implementation of a New Telerehabilitation System for Audiovisual Stimulation Training in Hemianopia – Full Text

Telerehabilitation, defined as the method by which communication technologies are used to provide remote rehabilitation, although still underused, could be as efficient and effective as the conventional clinical rehabilitation practices. In the literature, there are descriptions of the use of telerehabilitation in adult patients with various diseases, whereas it is seldom used in clinical practice with child and adolescent patients. We have developed a new audiovisual telerehabilitation (AVT) system, based on the multisensory capabilities of the human brain, to provide a new tool for adults and children with visual field defects in order to improve ocular movements toward the blind hemifield. The apparatus consists of a semicircular structure in which visual and acoustic stimuli are positioned. A camera is integrated into the mechanical structure in the center of the panel to control eye and head movements. Patients can use this training system with a customized software on a tablet. From hospital, the therapist has complete control over the training process, and the results of the training sessions are automatically available within a few minutes on the hospital website. In this paper, we report the AVT system protocol and the preliminary results on its use by three adult patients. All three showed improvements in visual detection abilities with long-term effects. In the future, we will test this apparatus with children and their families. Since interventions for impairments in the visual field have a substantial cost for individuals and for the welfare system, we expect that our research could have a profound socio-economic impact avoiding prolonged and intensive hospital stays.


Telerehabilitation, defined as the method by which communication technologies are used to provide remote rehabilitation, although still underused, could be as efficient and effective as the conventional clinical rehabilitation practices (1). In the literature, we can find some descriptions of the use of telerehabilitation in adult patients for various types of disorder, whereas it is seldom used in clinical practice with children and adolescents (2).

The development and use of telerehabilitation program are slow because they are affected by many logistical factors, such as regional economic resources, medical technical support systems, and population quality, but their potential is very high, as they are conceived and studied to improve patients’ ability to perform activities from daily life, thereby increasing their independence (3). For example, for adult post-stroke patients, telerehabilitation is widely used with the main goal of giving disabled people the same quality of motor, cognitive, and neuropsychological rehabilitation at home as they would have in-home visit and day-care rehabilitation (457).

So far, the application of telerehabilitation during childhood has been primarily limited to preterm babies (8) and children with hemiplegia (910), with autism spectrum disorders (11), with speech and language disorders (1213), and with learning difficulties (1416). Despite the well-known impact of visual defects on cognitive functioning and neurological recovery (17), no study has yet investigated the application of telerehabilitation with children with visual impairments.

Here, we describe an innovative telerehabilitation platform, which consists in an audiovisual telerehabilitation (AVT) system, developed for children and adults with visual field defects caused by post-chiasmatic brain lesions. The AVT system allows patients to exercise independently, in an intensive, active, and functional way and in a familiar environment, under remote supervision; it consists of a mobile device platform with remote control, which is accessible directly from home and suitable both for adults, adolescents, and children from the age of 8.

The AVT system is based on a very promising multisensory audiovisual therapy, originally developed for the treatment of adults and children with visual field defects caused by brain lesions (1819). Basically, this training aims to stimulate multisensory integration mechanisms in order to reinforce visual and spatial compensatory functions (i.e., implementation of oculomotor strategies). In this first phase of the study, we tested the feasibility and efficacy of AVT in three adult patients with chronic visual field defects, in order to explore how the apparatus can be implemented at home.[…]

Continue —>  Frontiers | Development and Implementation of a New Telerehabilitation System for Audiovisual Stimulation Training in Hemianopia | Neurology

Figure 1. Magnetic resonance imaging of the brain and visual field campimetry of S1, S2, and S3.


, , , ,

Leave a comment

[ARTICLE] How a diverse research ecosystem has generated new rehabilitation technologies: Review of NIDILRR’s Rehabilitation Engineering Research Centers – Full Text


Over 50 million United States citizens (1 in 6 people in the US) have a developmental, acquired, or degenerative disability. The average US citizen can expect to live 20% of his or her life with a disability. Rehabilitation technologies play a major role in improving the quality of life for people with a disability, yet widespread and highly challenging needs remain. Within the US, a major effort aimed at the creation and evaluation of rehabilitation technology has been the Rehabilitation Engineering Research Centers (RERCs) sponsored by the National Institute on Disability, Independent Living, and Rehabilitation Research. As envisioned at their conception by a panel of the National Academy of Science in 1970, these centers were intended to take a “total approach to rehabilitation”, combining medicine, engineering, and related science, to improve the quality of life of individuals with a disability. Here, we review the scope, achievements, and ongoing projects of an unbiased sample of 19 currently active or recently terminated RERCs. Specifically, for each center, we briefly explain the needs it targets, summarize key historical advances, identify emerging innovations, and consider future directions. Our assessment from this review is that the RERC program indeed involves a multidisciplinary approach, with 36 professional fields involved, although 70% of research and development staff are in engineering fields, 23% in clinical fields, and only 7% in basic science fields; significantly, 11% of the professional staff have a disability related to their research. We observe that the RERC program has substantially diversified the scope of its work since the 1970’s, addressing more types of disabilities using more technologies, and, in particular, often now focusing on information technologies. RERC work also now often views users as integrated into an interdependent society through technologies that both people with and without disabilities co-use (such as the internet, wireless communication, and architecture). In addition, RERC research has evolved to view users as able at improving outcomes through learning, exercise, and plasticity (rather than being static), which can be optimally timed. We provide examples of rehabilitation technology innovation produced by the RERCs that illustrate this increasingly diversifying scope and evolving perspective. We conclude by discussing growth opportunities and possible future directions of the RERC program.


Disabilities cause complex problems in society often unique to each person. A physical disability can limit a person’s ability to access buildings and other facilities, drive, use public transportation, or obtain the health benefits of regular exercise. Blindness can limit a person’s ability to interpret images or navigate the environment. Disabilities in speaking or writing ability may limit the effectiveness of communication. Cognitive disabilities can alter a person’s employment opportunities. In total, a substantial fraction of the world’s population – at least 1 in 6 people – face these individualized problems that combine to create major societal impacts, including limited participation. Further, the average person in the United States can expect to live 20% of his or her life with disability, with the rate of disability increasing seven-fold by age 65 [1].

In light of these complex, pervasive issues, the field of rehabilitation engineering asks, “How can technology help?” Answering this question is also complex, as it often requires the convergence of multiple engineering and design fields (mechanical, electrical, materials, and civil engineering, architecture and industrial design, information and computer science) with clinical fields (rehabilitation medicine, orthopedic surgery, neurology, prosthetics and orthotics, physical, occupational, and speech therapy, rehabilitation psychology) and scientific fields (neuroscience, neuropsychology, biomechanics, motor control, physiology, biology). Shaping of policy, generation of new standards, and education of consumers play important roles as well.

In the US, a unique research center structure was developed to try to facilitate this convergence of fields. In the 1970’s the conceptual model of a Rehabilitation Engineering Center (REC), focusing engineering and clinical expertise on particular problems associated with disability, was first tested. The first objective of the nascent REC’s, defined at a meeting held by the Committee on Prosthetic Research and Development of the National Academy of Sciences, was “to improve the quality of life of the physically handicapped through a total approach to rehabilitation, combining medicine, engineering, and related science” [2]. This objective became a working definition of Rehabilitation Engineering [2].

The first five centers focused on topics including functional electrical stimulation, powered orthoses, neuromuscular control, the effects of pressure on tissue, prosthetics, sensory feedback, quantification of human performance, total joint replacement, and control systems for powered wheelchairs and the environment [2]. The first two RECs were funded by the Department of Health, Education, and Welfare in 1971 at Rancho Los Amigos Medical Center in Downey, CA, and Moss Rehabilitation Hospital in Philadelphia. Three more were added the following year at the Texas Institute for Rehabilitation and Research in Houston, Northwestern University/the Rehabilitation Institute of Chicago, and the Children’s Hospital Center in Boston, involving researchers from Harvard and the Massachusetts Institute of Technology [3]. The Rehabilitation Act of 1973 formally defined REC’s and mandated that 25 percent of research funding under the Act go to them [2]. The establishment of these centers was stimulated by “the polio epidemic, thalidomide tragedy and the Vietnam War, as well as the disability movement of the early 70s with its demands for independence, integration and employment opportunities” [3].

After the initial establishment of these RECs, the governmental funding agency evolved into the National Institute on Disability and Rehabilitation Research (NIDRR, a part of the U.S. Department of Education), and now is the National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR, a part of the U.S. Department of Health and Human Services. Today, as we describe below, the RERC’s study a diverse set of technologies and their use by people with a disability, including human-computer interaction, mobile computing, wearable sensors and actuators, robotics, computer gaming, motion capture, wheeled mobility, exoskeletons, lightweight materials, building and transportation technology, biomechanical modeling, and implantable technologies. For this review, we invited all RERCs that were actively reporting to NIDILRR at the onset of this review project in 2015, and had not begun in the last two years, to participate. These were centers that were funded (new or renewal) in the period 2008-2013, except the RERC Wheelchair Transportation Safety, which was funded from 2001-2011. Two of the RERCs did not respond (see Table 1). For each center, we asked it to describe the user needs it targets, summarize key advances that it had made, and identify emerging innovations and opportunities. By reviewing the scope of rehabilitation engineering research through the lens of the RERCs, our goal was to better understand the evolving nature and demands of rehabilitation technology development, as well as the influence of a multidisciplinary structure, like the RERCs, in shaping the producing of such technology. We also performed an analysis of how multidisciplinary the current RERCs actually are (see Table 3), and asked the directors to critique and suggest future directions for the RERC program.[…]

Continue —>  How a diverse research ecosystem has generated new rehabilitation technologies: Review of NIDILRR’s Rehabilitation Engineering Research Centers | Journal of NeuroEngineering and Rehabilitation | Full Text

Fig. 14 Some MARS RERC projects. a) The KineAssist MX® Gait and Balance Device b) The Armeo Spring® reaching assistance device c) The March Hare virtual reality therapy game d) The Lokomat® gait assistance robot e) Robotic Error Augmentation between the therapist and patient f) lever drive wheelchair g) Ekso® exoskeleton h) Body-machine interface for device control

, , , , , , , , , , , , ,

Leave a comment

[Abstract+References] A Home-Based Telerehabilitation Program for Patients With Stroke 

Background. Although rehabilitation therapy is commonly provided after stroke, many patients do not derive maximal benefit because of access, cost, and compliance. A telerehabilitation-based program may overcome these barriers. We designed, then evaluated a home-based telerehabilitation system in patients with chronic hemiparetic stroke. Methods. Patients were 3 to 24 months poststroke with stable arm motor deficits. Each received 28 days of telerehabilitation using a system delivered to their home. Each day consisted of 1 structured hour focused on individualized exercises and games, stroke education, and an hour of free play. Results. Enrollees (n = 12) had baseline Fugl-Meyer (FM) scores of 39 ± 12 (mean ± SD). Compliance was excellent: participants engaged in therapy on 329/336 (97.9%) assigned days. Arm repetitions across the 28 days averaged 24,607 ± 9934 per participant. Arm motor status showed significant gains (FM change 4.8 ± 3.8 points, P = .0015), with half of the participants exceeding the minimal clinically important difference. Although scores on tests of computer literacy declined with age (r = −0.92; P < .0001), neither the motor gains nor the amount of system use varied with computer literacy. Daily stroke education via the telerehabilitation system was associated with a 39% increase in stroke prevention knowledge (P = .0007). Depression scores obtained in person correlated with scores obtained via the telerehabilitation system 16 days later (r = 0.88; P = .0001). In-person blood pressure values closely matched those obtained via this system (r = 0.99; P < .0001). Conclusions. This home-based system was effective in providing telerehabilitation, education, and secondary stroke prevention to participants. Use of a computer-based interface offers many opportunities to monitor and improve the health of patients after stroke.

1. Winstein CJStein JArena R, . Guidelines for adult stroke rehabilitation and recovery: a guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke. 2016;47:e98e169Google Scholar CrossrefMedline
2. Lang CEMacdonald JRReisman DS, . Observation of amounts of movement practice provided during stroke rehabilitation. Arch Phys Med Rehabil. 2009;90:16921698Google Scholar CrossrefMedline
3. Bernhardt JChan JNicola ICollier JM. Little therapy, little physical activity: rehabilitation within the first 14 days of organized stroke unit care. J Rehabil Med. 2007;39:4348Google Scholar CrossrefMedline
4. Kimberley TJSamargia SMoore LGShakya JKLang CE. Comparison of amounts and types of practice during rehabilitation for traumatic brain injury and stroke. J Rehabil Res Dev. 2010;47:851862Google Scholar CrossrefMedline
5. Laver KESchoene DCrotty MGeorge SLannin NASherrington C. Telerehabilitation services for stroke. Cochrane Database Syst Rev. 2013;(12):CD010255Google Scholar Medline
6. Agostini MMoja LBanzi R, . Telerehabilitation and recovery of motor function: a systematic review and meta-analysis. J Telemed Telecare. 2015;21:202213Google Scholar Link
7. Brennan DTindall LTheodoros D, . A blueprint for telerehabilitation guidelines. Int J Telerehabil. 2010;2:3134Google Scholar CrossrefMedline
8. Demiris GShigaki CLSchopp LH. An evaluation framework for a rural home-based telerehabilitation network. J Med Syst. 2005;29:595603Google Scholar CrossrefMedline
9. Bayley MTHurdowar ATeasell R, . Priorities for stroke rehabilitation and research: results of a 2003 Canadian Stroke Network consensus conference. Arch Phys Med Rehabil. 2007;88:526528Google Scholar CrossrefMedline
10. Wolf SLWinstein CJMiller JP, . Effect of constraint-induced movement therapy on upper extremity function 3 to 9 months after stroke: the EXCITE randomized clinical trial. JAMA. 2006;296:20952104Google Scholar CrossrefMedline
11. Wu JQuinlan EBDodakian L, . Connectivity measures are robust biomarkers of cortical function and plasticity after stroke. Brain. 2015;138(pt 8):23592369Google Scholar CrossrefMedline
12. Jimison HGorman PWoods S, . Barriers and Drivers of Health Information Technology Use for the Elderly, Chronically Ill, and Underserved. Rockville, MDAgency for Healthcare Research and Quality2008. Evidence Report/Technology Assessment No. 175. AHRQ Publication No. 09-E004. Google Scholar
13. Woldag HHummelsheim H. Evidence-based physiotherapeutic concepts for improving arm and hand function in stroke patients: a review. J Neurol. 2002;249:518528Google Scholar CrossrefMedline
14. Takahashi CDDer-Yeghiaian LLe VMotiwala RRCramer SC. Robot-based hand motor therapy after stroke. Brain. 2008;131(pt 2):425437Google Scholar CrossrefMedline
15. Kleim JAJones TA. Principles of experience-dependent neural plasticity: implications for rehabilitation after brain damage. J Speech Lang Hear Res. 2008;51:S225S239Google Scholar CrossrefMedline
16. Cramer SCSur MDobkin BH, . Harnessing neuroplasticity for clinical applications. Brain. 2011;134(pt 6):15911609Google Scholar CrossrefMedline
17. Cramer SCRepairing the human brain after stroke: I. Mechanisms of spontaneous recovery. Ann Neurol. 2008;63:272287Google Scholar CrossrefMedline
18. Dobkin BHDorsch A. The promise of mHealth: daily activity monitoring and outcome assessments by wearable sensors. Neurorehabil Neural Repair. 2011;25:788798Google Scholar Link
19. See JDodakian LChou C, . A standardized approach to the Fugl-Meyer assessment and its implications for clinical trials. Neurorehabil Neural Repair. 2013;27:732741Google Scholar Link
20. Mackay JCharles STKemp BHeckhausen J. Goal striving and maladaptive coping in adults living with spinal cord injury: associations with affective well-being. J Aging Health. 2011;23:158176Google Scholar Link
21. Sherbourne CDStewart AL. The MOS social support survey. Soc Sci Med. 1991;32:705714Google Scholar CrossrefMedline
22. Lewis SCDennis MSO’Rourke SJSharpe M. Negative attitudes among short-term stroke survivors predict worse long-term survival. Stroke. 2001;32:16401645Google Scholar CrossrefMedline
23. Williams LSWeinberger MHarris LEClark DOBiller J. Development of a stroke-specific quality of life scale. Stroke. 1999;30:13621369Google Scholar CrossrefMedline
24. Bunz U. The Computer-Email-Web (CEW) Fluency Scale: development and validation. Int J Hum Comput Interact. 2004;17:479506Google Scholar Crossref
25. Duncan PWallace DLai SJohnson DEmbretson SLaster L. The Stroke Impact Scale version 2.0: evaluation of reliability, validity, and sensitivity to change. Stroke. 1999;30:21312140Google Scholar CrossrefMedline
26. Jones FPartridge CReid F. The Stroke Self-Efficacy Questionnaire: measuring individual confidence in functional performance after stroke. J Clin Nurs. 2008;17(7B):244252Google Scholar CrossrefMedline
27. Zondervan DKFriedman NChang E, . Home-based hand rehabilitation after chronic stroke: Randomized, controlled single-blind trial comparing the MusicGlove with a conventional exercise program. J Rehabil Res Dev. 2016;53:457472Google Scholar CrossrefMedline
28. Page SJFulk GDBoyne P. Clinically important differences for the upper-extremity Fugl-Meyer Scale in people with minimal to moderate impairment due to chronic stroke. Phys Ther. 2012;92:791798Google Scholar CrossrefMedline
29. van der Lee JBeckerman HLankhorst GBouter LThe responsiveness of the Action Research Arm test and the Fugl-Meyer Assessment scale in chronic stroke patients. J Rehabil Med. 2001;33:110113Google Scholar CrossrefMedline
30. Baranowski TBuday RThompson DIBaranowski J. Playing for real: video games and stories for health-related behavior change. Am J Prev Med. 2008;34:7482Google Scholar CrossrefMedline
31. Brox EFernandez-Luque LTøllefsen T. Healthy gaming—video game design to promote health. Appl Clin Inform. 2011;2:128142Google Scholar CrossrefMedline
32. Lieberman D. Designing serious games for learning and health in informal and formal settings. In: Ritterfeld MVorderer P eds. Serious Games: Mechanisms and Effects. New York, NYRouteledge; 2009:117130Google Scholar
33. Chou Y. Actionable Gamification—Beyond Points, Badges, and Leaderboards. Fremont, CAOctalysis Media2015Google Scholar
34. Winstein CJMiller JPBlanton S, . Methods for a multisite randomized trial to investigate the effect of constraint-induced movement therapy in improving upper extremity function among adults recovering from a cerebrovascular stroke. Neurorehabil Neural Repair. 2003;17:137152Google Scholar Link
35. Sluijs EMKok GJvan der Zee J. Correlates of exercise compliance in physical therapy. Phys Ther. 1993;73:771782; discussion 783-786. Google Scholar CrossrefMedline
36. Miller KKPorter REDeBaun-Sprague EVan Puymbroeck MSchmid AA. Exercise after stroke: patient adherence and beliefs after discharge from rehabilitation. Top Stroke Rehabil. 2017;24:142148Google Scholar CrossrefMedline
37. McCabe JMonkiewicz MHolcomb JPundik SDaly JJ. Comparison of robotics, functional electrical stimulation, and motor learning methods for treatment of persistent upper extremity dysfunction after stroke: a randomized controlled trial. Arch Phys Med Rehabil. 2015;96:981990Google Scholar CrossrefMedline
38. Griffith V. A Stroke in the Family. New York, NYDelacorte Press1970Google Scholar
39. Herrmann NSeitz DFischer H, . Detection and treatment of post stroke depression: results from the registry of the Canadian stroke network. Int J Geriatr Psychiatry. 2011;26:11951200Google Scholar Medline
40. Kothari RSauerbeck LJauch E, . Patients’ awareness of stroke signs, symptoms, and risk factors. Stroke. 1997;28:18711875Google Scholar CrossrefMedline
41. Zerwic JHwang SYTucco L. Interpretation of symptoms and delay in seeking treatment by patients who have had a stroke: exploratory study. Heart Lung. 2007;36:2534Google Scholar CrossrefMedline
42. Qureshi AISuri MFGuterman LRHopkins LN. Ineffective secondary prevention in survivors of cardiovascular events in the US population: report from the Third National Health and Nutrition Examination Survey. Arch Intern Med. 2001;161:16211628Google Scholar CrossrefMedline
43. Putrino D. Telerehabilitation and emerging virtual reality approaches to stroke rehabilitation. Curr Opin Neurol. 2014;27:631636Google Scholar CrossrefMedline
44. Chen JJin WZhang XXu WLiu X-NRen C-C. Telerehabilitation approaches for stroke patients: systematic review and meta-analysis of randomized controlled trials. J Stroke Cerebrovasc Dis. 2015;24:26602668Google Scholar CrossrefMedline
45. Nakayama HJorgensen HRaaschou HOlsen T. Recovery of upper extremity function in stroke patients: the Copenhagen Stroke Study. Arch Phys Med Rehabil. 1994;75:394398Google ScholarCrossrefMedline
46. Ottenbacher KJSmith PMIllig SBLinn RTOstir GVGranger CV. Trends in length of stay, living setting, functional outcome, and mortality following medical rehabilitation. JAMA. 2004;292:16871695Google Scholar CrossrefMedline
47. Tong XKuklina EVGillespie CGeorge MG. Medical complications among hospitalizations for ischemic stroke in the United States from 1998 to 2007. Stroke. 2010;41:980986Google ScholarCrossrefMedline

Source: A Home-Based Telerehabilitation Program for Patients With StrokeNeurorehabilitation and Neural Repair – Lucy Dodakian, Alison L. McKenzie, Vu Le, Jill See, Kristin Pearson-Fuhrhop, Erin Burke Quinlan, Robert J. Zhou, Renee Augsberger, Xuan A. Tran, Nizan Friedman, David J. Reinkensmeyer, Steven C. Cramer, 2017

, , , , ,

Leave a comment

[Conference paper] Kushkalla: A Web-Based Platform to Improve Functional Movement Rehabilitation – Full Text


Telerehabilitation is a growing alternative to traditional face-to-face therapy, which uses technological solutions to cover rehabilitation care in both clinical centers and in-home programs. However, the current telerehabilitation systems are limited to deliver a set of exercise programs for some specific locomotor disability, without including tools that allow a quantitative analysis of the rehabilitation progress, in real-time, as well as the medical condition of patients. This paper presents the design and development of a novel web-based platform, named “Kushkalla”, that allows to perform movement assessment for creating personalized home-based therapy routines, integrating hardware and software tools for a quantitative analysis of locomotor movements based on motion capture, preprocessing, monitoring, visualization, storage and analysis, in real-time. The platform combines two motion capture strategies, the Kinect-based and IMU-based motion capture. In addition, a set of 2D and 3D graphical models, virtual environments, based on WebGL technology, and videoconference module are included to allow the interaction between user and clinician for enhancing the capability of the clinician to direct rehabilitation therapies.


According to the World Health Organization, at least 15% of world people could present musculoskeletal disabilities, which present difficulties to access appropriate management even in diagnosis, treatment or follow-up stages. Particularly, it is estimated that between 76% and 85% of disabled people have not accessed to treatment programs in developing countries [17]. Conventionally, when a musculoskeletal disability is diagnosed, a clinical specialist designs a specific functional rehabilitation program, according to the analysis of the strength, flexibility and other biomechanical aspects of the patient; then, a team of therapists is responsible for its execution and follow-up. Both diagnosis and follow-up require quantifying those biomechanical aspects in order to guarantee that the designed program is suitable for the patient. This workflow demands an important number of therapists and technologies, such as strength platforms, to ensure the quality of the rehabilitation program. Additionally, the patient location could be a major obstacle for this purpose. This is the case of some rehabilitation programs to restore functional movements of elderly people, which are constantly suffering locomotor impairment caused by aging. Thus, functional movement rehabilitation programs evaluate the movement patterns from each patient to establish what parts of the human body may be treated. An improper movement pattern or imbalances throughout the human body allow determining postural and motor issues, which are used to develop different rehabilitation programs by the therapist. Therefore, functional movement rehabilitation programs are able to rehabilitate the human body that is weak, tight or unbalance by using a combination of functional movement correction and classic rehabilitation exercises.

Recently, telerehabilitation has emerged as an alternative that allows to perform functional movement rehabilitation activities from the comfort of the patient location, which are monitored by the physician from the specialized medical center [14]. This is possible by the use of the Internet and emerging technologies such as inertial sensors, optical motion capture devices, robots, virtual reality environments, among others [4]. In general, telerehabilitation strategies can be classified as: telepresence-based rehabilitation, which are supported by videoconference tools that allow a continuous communication between patient and physician [3]; robotic-based rehabilitation, which uses autonomous robots or exoskeletons for guiding patient movements [7]; interactive-based rehabilitation, which uses interactive environments for motivating patient to perform exercises while playing [121521] and; rehabilitation based on a precision analysis, which provides movement analysis tools for supporting the physician decisions [11].

This paper describes the design and development of a novel web-based platform that integrates telepresence, interactive environments, and movement analysis tools, for providing the technology to carry out functional movement assessment and to create personalized home-based therapy routines. The proposed Web-based platform was developed on a service-oriented architecture (SOA), a client/server software design approach in which an application consists of software services and software service consumers that are provided between software components through several network communication protocols [16]. It is composed of two main software parts: a client and a cloud server components. Additionally, two applications conform the client component: the patient application, and the physician application. The patient application includes a bimodal human motion capture module that allows to integrate both a wearable inertial sensor system and a depth camera sensor (Kinect); a visualization module provided with a virtual environment with an interactive interface in which patient can see in two 3D avatars how an exercise must be executed and how they execute it; and an assistance module provided with a videoconference tool and videotutorials about the platform. The Physician application includes an exercise visualization module, synchronized with the patient interface, in which real-time patient movements are displayed, and a motion analysis module, which displays graphically the movement measurements generated by the analysis of captured data. Finally, the server component, implemented as a software as a service cloud component that it includes a web-server, a websocket server, a webRTC (web with Real-Time Communications) server, and relational and non-relational databases.

This paper is organized as follows. The next section presents a brief summary of related works. In the Sect. 3 the main hardware/software components of the proposed platform are described. Section 4 presents a preliminary evaluation that shows the reliability of the proposed architecture and finally, Sect. 5 presents the conclusions and discuss the future work.[…]

Continue —>  Kushkalla: A Web-Based Platform to Improve Functional Movement Rehabilitation | SpringerLink

Fig. 1. General framework of Kushkalla: Telerehabilitation platform

, , , , ,

Leave a comment

[Abstract] Autonomous rehabilitation at stroke patients home for balance and gait: safety, usability and compliance of a virtual reality system.


Background: New technologies, such as telerehabilitation and gaming devices offer the possibility for patients to train at home. This opens the challenge of safety for the patient as he is called to exercise neither with a therapist on the patients’ side nor with a therapist linked remotely to supervise the sessions.

Aim: To study the safety, usability and patient acceptance of an autonomous telerehabilitation system for balance and gait (the REWIRE platform) in the patients home.

Design: Cohort study.

Setting: Community, in the stroke patients’ home.

Population: 15 participants with first-ever stroke, with a mild to moderate residual deficit of the lower extremities.

Method: Autonomous rehabilitation based on virtual rehabilitation was provided at the participants’ home for twelve weeks. The primary outcome was compliance (the ratio between days of actual and scheduled training), analysed with the two-tailed Wilcoxon Mann- Whitney test. Furthermore safety is defined by adverse events. The secondary endpoint was the acceptance of the system measured with the Technology Acceptance Model. Additionally, the cumulative duration of weekly training was analysed.

Results: During the study there were no adverse events related to the therapy. Patients performed on average 71% (range 39 to 92%) of the scheduled sessions. The Technology Acceptance Model Questionnaire showed excellent values for stroke patients after the training. The average training duration per week was 99 ±53min.

Conclusion: Autonomous telerehabilitation for balance and gait training with the REWIRE-system is safe, feasible and can help to intensive rehabilitative therapy at home.

Clinical Rehabilitation Impact: Telerehabilitation enables safe training in home environment and supports of the standard rehabilitation therapy.

Read Article at publisher’s site

Source: Autonomous rehabilitation at stroke patients home for balance and gait: safety, usability and… – Abstract – Europe PMC

, , , , , ,

Leave a comment

[REVIEW] Telerehabilitation: Review of the State-of-the-Art and Areas of Application – Full Text  


Background: Telemedicine applications have been increasing due to the development of new computer science technologies and of more advanced telemedical devices. Various types of telerehabilitation treatments and their relative intensities and duration have been reported.

Objective: The objective of this review is to provide a detailed overview of the rehabilitation techniques for remote sites (telerehabilitation) and their fields of application, with analysis of the benefits and the drawbacks related to use. We discuss future applications of telerehabilitation techniques with an emphasis on the development of high-tech devices, and on which new tools and applications can be used in the future.

Methods: We retrieved relevant information and data on telerehabilitation from books, articles and online materials using the Medical Subject Headings (MeSH) “telerehabilitation,” “telemedicine,” and “rehabilitation,” as well as “disabling pathologies.”

Results: Telerehabilitation can be considered as a branch of telemedicine. Although this field is considerably new, its use has rapidly grown in developed countries. In general, telerehabilitation reduces the costs of both health care providers and patients compared with traditional inpatient or person-to-person rehabilitation. Furthermore, patients who live in remote places, where traditional rehabilitation services may not be easily accessible, can benefit from this technology. However, certain disadvantages of telerehabilitation, including skepticism on the part of patients due to remote interaction with their physicians or rehabilitators, should not be underestimated.

Conclusions: This review evaluated different application fields of telerehabilitation, highlighting its benefits and drawbacks. This study may be a starting point for improving approaches and devices for telerehabilitation. In this context, patients’ feedback may be important to adapt rehabilitation techniques and approaches to their needs, which would subsequently help to improve the quality of rehabilitation in the future. The need for proper training and education of people involved in this new and emerging form of intervention for more effective treatment can’t be overstated.


In the last few years, telemedicine applications have been increasing due to the development of new computer science technologies and of more advanced telemedical devices. Long-distance communication can be easily achieved by videoconferencing, email, and texting, to name a few. Today there is the possibility of controlling robots, robotic arms, or drones at a distance. Thanks to these advancements, the course of human action has been considerably transformed [1]. During the last 20 years, demographic changes and increased budget allocation in public health have improved new rehabilitative practices [2]. Rehabilitation is an old branch of medicine, but in the last few years, new telecommunication-based practices have been developed all over the world. These particular approaches in the field of rehabilitation are commonly defined as telerehabilitation, which should be considered as a telemedicine subfield consisting of a system to control rehabilitation at a distance [3].

Telerehabilitation has been developed to take care of inpatients, transferring them home after the acute phase of a disease to reduce patient hospitalization times and costs to both patients and health care providers. Telerehabilitation allows for treatment of the acute phase of diseases by substituting the traditional face-to-face approach in the patient-rehabilitator interaction [4]. Finally, it can cover situations in which it is complicated for patients to reach traditional rehabilitation infrastructures located far away from where they live.

Controlled studies on rehabilitation have demonstrated that quick management of an injury or a disease is critical to achieve satisfactory results in terms of increasing a patient’s self-efficacy. Hence, a rehabilitation program should start as soon as possible, be as intensive as possible, be prolonged, and continue during the recovery phase. A major factor is the initiation time, which, in general, should begin as soon as possible. In most cases, the initial stages of rehabilitation, after the occurrence of a disease or injury, could be performed by patients at home even if they need accurate and intensive treatment. For these reasons, telerehabilitation was developed to achieve the same results as would be achieved by the normal rehabilitation process at a hospital or face to face with a physiotherapist. Various types of telerehabilitation treatments and their relative intensities and duration have been reported [5].

The first scientific publication on telerehabilitation is dated 1998 and, in the last few years, the number of articles on the topic has increased, probably because of the emerging needs of people and due to the development of exciting new communication and computer technologies. Figure 1 shows the number of patients treated through telerehabilitation from 1998 to 2008 according to studies published in the international literature [2].

A remarkable increase in the number of patients treated by telerehabilitation is noticeable from 2002 to 2004. After a subsequent decrease, the number of patients assisted by telerehabilitation increased starting from 2007, probably due to the support of new technologies and the overcoming of the initial skepticism to which every new technology is subjected.

Telerehabilitation is primarily applied to physiotherapy [6,7], and neural rehabilitation is used for monitoring the rehabilitative progress of stroke patients [8]. Telerehabilitation techniques mimic virtual reality [912] and rehabilitation for neurological conditions by using robotics and gaming techniques [13]. Quite often, telerehabilitation has been associated with other nonrehabilitative technologies such as remote monitoring of cardiovascular parameters, including electrocardiogram (ECG), blood pressure, and oxygen saturation in patients with chronic diseases [14]. These technologies belong to another telemedicine branch called telemonitoring, which has been widely developed and used in recent years. A few studies were also centered on the economic aspects of the use of telerehabilitation to reduce the costs of hospitalization [15]. We reviewed the status and future perspectives of telerehabilitation by analyzing their impact on patients’ everyday life. The main topics taken into account were (1) the status of telerehabilitation and analysis of the main medical specialties where it is being applied, (2) quality-of-life improvement due to telerehabilitation, and (3) the future of telerehabilitation.

Figure 1. Number of patients treated from 1998 to 2008 through telerehabilitation techniques.


Continue —> JRAT-Telerehabilitation: Review of the State-of-the-Art and Areas of Application | Peretti | JMIR Rehabilitation and Assistive Technologies

, , , ,

Leave a comment

[ARTICLE] Agent-based systems for telerehabilitation: strengths, limitations and future challenges (PDF Download Available) – Full Text

Telerehabilitation in older adults is most needed in the patient environments, rather than in formal ambulatories or hospitals. Supporting such practices brings significant advantages to patients, their family, formal and informal caregivers, clinicians, and researchers. Several techniques and technologies have been developed aiming at facilitating and enhancing the effectiveness of telerehabilitation. This paper gives a quick overview of the state of the art, investigating video-based, wear-able, robotic, distributed, and gamified telerehabilitation solutions. In particular, agent-based solutions are analyzed and discussed addressing strength, limitations, and future challenges. Elaborating on functional requirements expressed by professional physiotherapists and researchers, the need for extending multi-agent systems (MAS) peculiarities at the sensing level in wearable solutions establishes new research challenges. Employed in cyber-physical scenarios with users-sensors and sensors-sensors interactions, MAS are requested to handle timing constraints, scarcity of resources and new communication means, which are crucial for providing real-time feedback and coaching.
1 Introduction
Healthcare institutions are facing the strain of a significantly larger elderly population [1]. Lengthening life expectancy is met by an increasing demand for medical and technological contributions to extend the ”good-health”, and disability free period.
The major factor catalyzing the elderly’s impairing process is the progres-
sive reduction of mobility, due to the natural aging process, inactivity, dis-
eases such as osteoarthritis, stroke or other neurological conditions, falls with its consequences, such as fear of falls (leading to inactivity), or fractures (needing surgery).Despite the emergence of less-invasive surgical techniques, post-intervention rehabilitation still requires extended periods and tailored therapies, which usually involve complications. Performing traditional rehabilitative practices is leading to a significant increase in public-health costs and, in some cases a lack of resources, thus worsening the services’ quality. Rehabilitation is often a long process and needs to be sustained long after the end of the acute care. Simplifying the access to health services [2] can raise the number of patients, maintaining (or even increasing) the quality of care. For example, patients requiring support, such as continuous or selective monitoring, can benefit from systems that automatically transmit the information gathered in their domestic environment to the health clinics, thus enabling telemonitoring on their health conditions [3].
Although in traditional solutions telemonitoring is a self-contained practice
limited to passively observing the patients, the need for remote sensing is crucially coupled with the need for coaching older adults in their daily living [4,5].
For example, a critical activity such as telerehabilitation cannot be limited
to observing the patients’ behaviors. Indeed, patient adherence and acceptability of rehabilitative practices need to be actively enhanced, overcoming pitfalls due to motor (e.g., endurance), non-motor (e.g., fatigue, pain, dysautonomic symptoms, and motivational), and cognitive deficits. According to Rodriguez et al. [6], telerehabilitation can be formally defined as:
“the application of telecommunication, remote sensing and operation tech-
nologies, and computing technologies to assist with the provision of med-
ical rehabilitation services at a distance.”
Patients, physiotherapists, and health institutes can gain several benefits
from an extensive adoption of telerehabilitation systems [7]. Considering the
economical point of view, Mozaffarian et al. [8] figured out that the total cost
of stroke in the US was estimable to be 34.3 billion dollars in 2008, rising up to 69.1 billion dollars in 2016.
Even though to date they are not precisely quantifiable due to insufficient evidence [9], Mutingi et al. [10] presented as “inevitable advantages”
(i) a substantial cost saving primarily due to the reduction of specialized human resources,
(ii) an enhancement of patient comfort and lifestyle, and (iii) improvements of therapy and decision making processes. Moreover, Morreale et al. [11] mentioned one of the most appreciated benefits: the increase of adherence to rehabilitation protocols.
The multitude of scientific contributions fostering telerehabilitation exploits
new technologies and various architectures to better understand and serve user requirements. However, due to technological or technical limitations, physiotherapists’ needs have not yet been completely satisfied. To fill this gap, a system evolution is required. For example, telerehabilitation systems cannot offer the same behavior to users with diverse conditions. Viceversa, according to the environment condition, they must rather be able to adapt themselves to the user needs [6].
Telerehabilitation is characterized by a very delicate equilibrium between
environment, devices, and users. Thus, the capabilities such as self adaptation, flexibility, and ubiquity are crucial to facilitate and promote the usability and then the actual practices.
Agent-based systems for telerehabilitation: strengths, limitations and future challenges (PDF Download Available). Available from: [accessed May 26, 2017].

Continue —> Agent-based systems for telerehabilitation: strengths, limitations and future challenges (PDF Download Available)

Fig. 2. Agent-based sensing: future challenge for telerehabilitation MAS. 

, , , , , ,

Leave a comment

[ARTICLE] Towards a New Wave of Telerehabilitation Applications – Full Text PDF


In recent years, new scenarios for experimenting telerehabilitation services have been opening thanks to the diffusion of the new technologies. The revolution brought about by the Internet of Things and Big Data Analytics is having an effect also in the field of telerehabilitation services. The literature has broadened in scope and grown in volume and, in certain aspects, the focus of research has changed in the last few years. This article examines the major changes that have come about in the field of telerehabilitation, which can essentially be divided into two main strands: low-cost end-user applications, and the integration of telerehabilitation services. We will briefly review the emerging investigations and experimentations in the field of telerehabilitation, analyzing the market trends in the sector and the commercial strategies of companies working in it, and aim to outline the most relevant challenges that exist for the delivery of effective and sustainable telerehabilitation services. Our opinion is that telerehabilitation currently represents a very promising field, although many questions still remain open, for which concrete and reliable answers are required. In this respect, we focus on a fundamental issue that underlies the field of telerehabilitation services, namely the influence that environment has on the effectiveness of treatment. In short, how can the type of environment affect the results of treatment?

The Telerehabilitation Scenario

Many different terms are used to designate the application of ICTs in the field of healthcare. The term medical informatics, first coined around 1970, was superseded at the end of the 1990s by eHealth, while, nowadays, telemedicine, tele health, and tele care are all used fairly interchangeably.

The main advantages of Telemedicine in healthcare are evident [1-3]. It is a form of secondary prevention encompassing services dedicated to persons classified as at risk or suffering from chronic diseases (e.g. diabetes or cardiovascular disease) who require a constant monitoring of vital parameters in order to reduce the risk of complications, such as that of blood glucose levels for diabetic patients. Meanwhile, Tele-diagnosis focuses on moving diagnostic information rather than the patient. Although a complete diagnosis cannot be performed exclusively through the use of ICT tools, computer-based systems can effectively support diagnostic processes, for example by giving the possibility of exchanging data amongst specialists and facilitating its communication.

Home health monitoring services utilise ITC-based technology to monitor patients in their homes by means of devices that measure vital data, such as blood pressure, glucose levels, pulse, blood oxygen levels, etc., and enable the transmission of this data to clinicians [4,5].

Recently, the concept of telerehabilitation has been introduced to refer to the provision of rehabilitation care at a distance. Telerehabilitation, or e-rehabilitation, is considered a subcomponent of the broader area of telemedicine [6], and can be divided into three main categories: image based telerehabilitation, sensor based telerehabilitation, and telerehabilitation based on virtual technologies [7]. Lately, the notion of social telerehabilitation has been introduced to distinguish the application of ICT to the social rehabilitation sphere [8,9].

Telerehabilitation is widely considered to be advantageous in the treatment of patients. Telerehabilitation services are seen as being a costeffective alternative to traditional rehabilitation services since they can be delivered at a distance, thus reducing the travel costs and difficulties for patients to receive care at a healthcare facility.

The increasing interest in telerehabilitation is closely related to the diffusion of the internet. Indeed, thanks to the internet, all traditional sectors, including healthcare, are going through processes of transformation in order to become more effective and accurate, as well as cheaper and more powerful.

Telerehabilitation solutions have been experimented in many areas, particularly that of rehabilitation following traumatic injury (for assessment, physical therapy, and monitoring). …

Full Text PDF

, , ,

Leave a comment

[ARTICLE] User-centered design of a patient’s work station for haptic robot-based telerehabilitation after stroke – Full Text


Robotic therapy devices have been an important part of clinical neurological rehabilitation for several years. Until now such devices are only available for patients receiving therapy inside rehabilitation hospitals. Since patients should continue rehabilitation training after hospital discharge at home, intelligent robotic rehab devices could help to achieve this goal. This paper presents therapeutic requirements and early phases of the user-centered design process of the patient’s work station as part of a novel robot-based system for motor telerehabilitation.

1 Introduction

Stroke is one of the dominant causes of acquired disability [1] and it is the second leading cause of death worldwide [2]. The high incidence of the disease and the current demographic developments are likely to increase the number of stroke patients in the future. Most of the survivors have physical, cognitive and functional limitations and require intensive rehabilitation in order to resume independent everyday life [3]. Therefore, the main goal of motor rehabilitation is relearning of voluntary movement capability, a process which takes at least several months, some improvement can occur even after years. In the rehabilitation clinic, patients usually receive a daily intensive therapy program. However, for further improvement of motor abilities, severely affected patients are required to continue their rehabilitation training outside the rehabilitation settings, after being discharged from the rehabilitation clinic. Langhammer and Stanghelle [4] found that a lack of follow-up rehabilitation treatment at home leads to deterioration of activities of daily living (ADL) and to motor functions in general. A possible solution is an individualized and motivating telerehabilitation system in the patient’s domestic environment. Some studies [5], [6] have confirmed the advantage of home rehabilitation after stroke and showed that telerehabilitation received high acceptance and satisfaction, both from patients, as well as from health professionals [7]. Most of the existing telesystems [7], [8] are based on audio-visual conferencing or on virtual environments and contain rather simple software for monitoring patients’ condition. However, in neurological rehabilitation the sensorimotor loop needs to be activated by provision of physiological haptic feedback (touch and proprioception) [3].

Robot-based rehabilitation is currently one of the most prevalent therapeutic approaches. It is often applied in hospitals alongside conventional therapy and is beneficial for motor recovery [9]. Rehabilitation training including a haptic-therapy device may therefore be even more promising for home environments than non-haptic telerehabilitation. Several telerehabilitation systems, which include not only audio and visual, but also haptic modality, already exist [10], [11] . Most of these solutions use low-cost commercial haptic devices (e.g. joysticks) for therapy training, with the goal of cost minimization and providing procurable technology. Nonetheless, devices specifically developed for stroke rehabilitation, which are already established in clinical settings, may have greater impact on motor relearning and could therefore also be more effective at home, compared with existing home rehabilitation devices.

In a previous paper [12], we presented a concept and design overview of a haptic robot-based telerehabilitation system for upper extremities which is currently under development. In the present work, we describe therapeutic requirements, user-centred development [13] and implementation of the patient’s station of the telesystem.

Continue —> User-centered design of a patient’s work station for haptic robot-based telerehabilitation after stroke : Current Directions in Biomedical Engineering

Figure 3 Implementation of the patient’s work station based on Reha-Slide (left) and Bi-Manu-Track (right).

, , , , , , , ,

Leave a comment

[Abstract] GEAR: A Mobile Game-Assisted Rehabilitation System


Rehabilitation exercises are an important means for gaining mobility and strength after injuries or surgery. Self-exercising in between physio-therapy sessions is vital for effective rehabilitation. Yet, many people do not follow exercise regimes, which can hamper their recovery. This study proposes GEAR – a mobile GamE Assisted Rehabilitation system – to engage users in self-exercising and to improve adherence to their exercise regime. The system consists of a wearable wristband to monitor users’ movements, a mobile game that incorporates the exercises, and a dashboard to monitor and visualize users’ exercise performance. GEAR has advantages of portability and lower cost as compared to PC or Kinect-based rehabilitation systems. This study describes GEAR and reports on a pilot assessment of its interface and system. The pilot test demonstrates the feasibility of GEAR and provides feedback that is being used to enhance the system prior to full-scale evaluation.

Source: GEAR: A Mobile Game-Assisted Rehabilitation System – IEEE Xplore Document

, , , , , , ,

Leave a comment

%d bloggers like this: