Posts Tagged Tele-rehabilitation

[Abstract] An Automated Game-Based Variable-Stiffness Exoskeleton for Hand Rehabilitation – Full Text PDF


In this paper, we propose and demonstrate the functionality of a novel exoskeleton which provides variable resistance training for human hands. It is intended for people who suffer from diminished hand strength and low dexterity due to non-severe forms of neuropathy or other ailments. A new variable-stiffness mechanism is designed based on the concept of aligning three different sized springs to produce four different levels of stiffness, for variable kinesthetic feedback during an exercise. Moreover, the design incorporates an interactive computer game and a flexible sensor-based glove that motivates the patients to use the exoskeleton. The patients can exercise their hands by playing the game and see their progress recorded from the glove for further motivation. Thus the rehabilitation training will be consistent and the patients will re-learn proper hand function through neuroplasticity. The developed exoskeleton is intrinsically safe when compared with active exoskeleton systems since the applied compliance provides only passive resistance. The design is also comparatively lighter than literature designs and commercial platforms.

Download Full Text PDF

via An Automated Game-Based Variable-Stiffness Exoskeleton for Hand Rehabilitation – Volume 9, No. 4, April 2020 – IJMERR

, , , , , , ,

Leave a comment

[THESIS] Multi-sensors for realization of home tele-rehabilitation


Research in assistive healthcare, in particular home rehabilitation, has spawn huge potential owing to the recent advancement of internet-of-things technology and the wearable hardware, Inertial Measurement Unit (IMU) in wearable sensors and smartphones become a affordable for community usage. However, using low cost IMU sensors or smartphones face certain challenges, such as accurate orientation estimation for lower-limb motion tracking, which is usually less of a problem in specialized motion tracking sensor devices. To address these issues, the candidate has made three main contributions: a new and better orientation estimation algorithm which combines quaternion-based Kalman filter with corrector estimates using gradient descent (KFGD), an auto-detector of post-filtered lower-limb orientation signal oscillation and the machine-learning based state identification of rehabilitation exercise. Firstly, obtaining accurate orientation readings with noise-prone IMU and post-processing drift is a key challenge in motion tracking research. It is the result of accumulated errors over the integration of the gyroscope signal to calculate the angular displacement, in other words, the orientation of the limb, in the motion tracking application. Thus, the candidate proposes two sensor fusion algorithms: the complementary filter feedback (CFF) and the quaternion-based Kalman filter with corrector estimates using gradient descent (KFGD). The complementary filter feedback (CFF) focuses on the components’ performance of high-pass filter (from angular velocity) and low-pass filter (from fusion of gravity and earth magnetic field). These components contribute to the estimated orientation while the proposed feedback loop can correct the drift. KFGD is later introduced to further improve the limitation of the low-pass filter and the fixed fusion threshold of the CFF. Gradient descent method and quaternion-based Kalman Filter are chosen for their progressive features. The performance was evaluated on the case study of early stage rehabilitation exercises, namely, leg extension and sit-to-stand. The result shows that CFF is capable of fast motion tracking and confirms that the feedback loop is capable of correcting errors caused by integration of gyroscope data. KFGD outperforms the state-of-the-art Madgwick algorithm and is recommended for obtaining accurate orientation readings using motion sensors. Secondly, upon observing the characteristics of the post-filtered orientation signals of the lower-limb, a noticeable artifact in the output signal that it would oscillate from positive to negative and vice versa. To address the oscillations in the signals of both motion capture and inertial measurement sensors, the candidate applied machine learning algorithms and compared them with the rule-based approach. Machine learning methods, such as Logistic Regression, Support Vector Machine and Multilayer perceptron, were adopted in order to automatically detect the oscillation. The results showed that machine learning methods are able to learn the oscillation patterns in wearable sensor data and identify the tendency of fluctuation thereby allowing the errors to be filtered out more efficiently than rule-based method. Lastly, in order to realize meaningful home rehabilitation, there is a need for informative feedback or intervention in parallel with the exercise monitoring. The study aims to use the collected data and the understanding of wearable signal to simulate the high-level observations by the physiotherapist towards the patients and provide informative feedback during exercising at home. Therefore, the candidate proposes the study on machine-learning based state identification of rehabilitation exercise by using wearable sensors on the lower limbs. The informative feedback and quality assessment could be obtained by selectively segmenting the exercise into four states: rest, raise, hold and drop. The segmentation potentially increases the frequency of detection resulting in almost real-time feedback. In addition, identifying the abnormal sequences against the correct pattern in the respective state results in more specific and informative feedback. In this work, the candidate analyses the impact and derives valuable insights of the extracted sensor signals in relation to the predicted. As a result, the predictive model yields up to 95.89% (SVM) and 94.04% (SVM) accuracy for binary and multi-label pattern recognition respectively. The experiment and recommended framework show the efficiency and potential of using signal data as features in motion-based exercise pattern recognition. The work presented in this thesis demonstrates the realization of home rehabilitation from the hardware-level to the simulation of user intervention. The methodologies exploit the a ordable hardware to correctly track the limb motion while the motion signal prediction model and analysis boost the potential of intervention strategy for the user’s home exercise feedback.

Download Full Text PDF

via Multi-sensors for realization of home tele-rehabilitation | DR-NTU

, , , ,

Leave a comment

[Abstract] Information Management in IoT Cloud-Based Tele-Rehabilitation as a Service for Smart Cities: Comparison of NoSQL Approaches



Nowadays, recent advancements in ICT have sped up the development of new services for smart cities in different application domains. One of these is definitely healthcare. In this context, remote patient monitoring and rehabilitation activities can take place either in satellite hospital centres or directly in citizens’ homes. Specifically, using a combination of Cloud computing, Internet of Things (IoT) and big data analytics technologies, patients with motor disabilities can be remotely assisted avoiding stressful waiting times and overcoming geographical barriers. This paper focuses on the Tele-Rehabilitation as a Service (TRaaS) concept. Such a service generates healthcare big data coming from remote rehabilitation devices used by patients that need to be processed in the hospital Cloud. Specifically, after a feasibility analysis, by using a Lokomat dataset as sample, we measured and compared the performances of four of the major NoSQL DBMS(s) demonstrating that the document approach well suits our case study.


via Information Management in IoT Cloud-Based Tele-Rehabilitation as a Service for Smart Cities: Comparison of NoSQL Approaches – ScienceDirect

, , , , , , , , ,

Leave a comment



Tele-Rehabilitation Interventions through University-based Medicine for Prevention and Health

Download PDF File

, , ,

Leave a comment

[ARTICLE] A Systematic Review of Usability and Accessibility in Tele-Rehabilitation Systems – Full Text


The appropriate development of tele-rehabilitation platforms requires the involvement and iterative assessments of potential users and experts in usability. Usability consists of measuring the degree to which an interactive system can be used by specified final users to achieve quantified objectives with effectiveness, efficiency, and satisfaction in a quantified context of use. Usability studies need to be complemented by an accessibility assessment. Accessibility indicates how easy it is for a person to access any content, regardless of their physical, educational, social, psychological, or cultural conditions. This chapter intends to conduct a systematic review of the literature on usability and accessibility in tele-rehabilitation platforms carried out through the PRISMA method. To do so, we searched in ACM, IEEE Xplore, Google Scholar, and Scopus databases for the most relevant papers of the last decade. The main result of the usability shows that the user experience predominates over the heuristic studies, and the usability questionnaire most used in user experience is the SUS. The main result of the accessibility reveals that the topic is only marginally studied. In addition, it is observed that Web applications do not apply the physical and cognitive accessibility standards defined by the WCAG 2.1.

1. Introduction

Innovation and technological advances involve the offering of valuable products and services to improve the quality of life of citizens. In recent decades, the domain of telemedicine has reported advances in the control, monitoring and evaluation of various clinical conditions [1]. In the field of rehabilitation, numerous studies and state-of-the-arts from informatics perspective [2] and different areas of application [34], show the effectiveness and advantages of the use of remote rehabilitation (or tele-rehabilitation) [56]. Tele-rehabilitation aims to reduce the time and costs of offering rehabilitation services. The main objective is to improve the quality of life of patients [7]. Tele-rehabilitation cannot replace traditional neurological rehabilitation [8]. It is considered as a partial replacement of face-to-face physical rehabilitation [9]. Tele-rehabilitation uses mainly two groups of technologies: (1) wearable devices and (2) vision-based systems based on depth cameras and intelligent algorithms [10]. In [5], the authors describe and analyze some characteristics and typical requirements tele-rehabilitation systems.

Design and conception of tele-rehabilitations platforms that do not consider guidelines, metrics, patterns, principles, or practice success factors can affect the access to the service, the effectiveness, quality, and usefulness. It can cause problems of confusion, error, stress, and abandonment of the rehabilitation plan. Therefore, guaranteeing the correct use of these applications implies to incorporate different studies of usability in the life cycle of the interactive system. For this reason, aspects of human factors engineering in tele-rehabilitation systems have been studied with the aim of providing accessible, efficient, usable and understandable systems [1112].

User-centered agile development (UCD) approaches allows developers to specify and design the set of interfaces of any interactive system in a flexible and effective way [1314]. The agile development life cycle centered on user experience (UX-ADLC) allows iteratively evaluating system interfaces based on the results of the previous iteration. The evaluation also includes the errors and usability problems encountered [15]. Thus, usability studies are an essential aspect of technology development [16]. This is the reason why designers need to meet usability and user experience objectives while adhering to agile principles of software development. Formative and summative usability tests are methods of evaluating software products widely adopted in user-centered design (UCD) [15] and agile UX development lifecycle. Both approaches are frequently used in the development of software applications. Rapid formative usability should be carried out so as to fulfill UX goals while satisfying end users’ needs. Formative usability is used as an iterative test-and-refine method performed in the early steps of a design process, in order to detect and fix usability problems [15]. Summative usability allows for assuring, in later phases of the design, the quality of the user experience (UX) for a software product in development. The focus is on short work periods (or iterations) where usability tests (formative and summative) must be contemplated. This means that quick formative usability tests should be carried out to fulfill UX goals [17].

The ISO 9241-11 standard [18] is a framework for understanding and applying the concept of usability to situations in which people use interactive systems and other types of systems (including built environments), products (including industrial and consumer products) and services (including technical and personal services). Likewise, the usability standard ISO 9241-11 facilitates the measurement of the use of a product with the aim of achieving specific objectives with effectiveness, efficiency and satisfaction in a context of specific use [18].

Usability can be studied through software evaluation methods widely accepted in user centered design (UCD) [15]. It can be formative or summative [8]. Formative usability consists of a set of iterative tests carried out in the early stages of the design process. The aim of the tests is to refine and improve the software product, as well as to detect and solve potential usability problems. As a complement, the summative usability allows to obtain an evaluation of the user experience (UX) for a software product in development. Formative usability facilitates decision making during the design and development of the product, while summative usability is useful when studying user experience (UX).

Tullis and Stetson [19] evaluated the effectiveness of the most used questionnaires to measure the summative usability. The authors found that the System Usability Scale (SUS) [20] and the IBM Computer System Usability Questionnaire (CSUQ) [21] are the most effective. SUS provides a quick way for measuring the usability through user experience. It consists of a 10-item questionnaire with 5-likert scale range from “Strong Agree” to “Strongly Disagree.” The CSUQ focuses on three main aspects: (1) the utility, which refers to the opinion of users regarding the ease of use, the ease of learning, the speed to perform the operations, the efficiency in completing tasks and subjective feeling; (2) the quality of the information which studies the subjectivity of the user regarding the management of system errors, the clarity of the information and the intelligibility; and finally, (3) the quality of the interface which measures the affective component of the user’s attitude in the use of the system.

Large part of the tasks in the tele-rehabilitation systems are carried out by patients who require to treat a temporary disability. Considering the special needs of these users, usability evaluations alone cannot guarantee an appropriate design of the system. On the contrary, accessibility studies can provide the mechanisms to offer the same means of use to all users of any interactive system. A study combining usability and accessibility was presented in [22]. The study analyzes how remote and/or video monitoring technologies affect the accessibility, effectiveness, quality and usefulness of the services offered by tele-rehabilitation systems. To do this, the authors provide an overview of the fundamentals necessary for the analysis of usability, in addition to analyzing the strengths and limitations of various tele-rehabilitation technologies, considering how technologies interact with the clinical needs of end users such as accessibility, effectiveness, quality and utility of the service [22].

For many people, the Web is a fundamental part of everyday life. Therefore, a fundamental aspect to ensure the inclusivity of a Website is its accessibility. For example, people who cannot use their arms to write on their computer can use a mouth pencil [23]. Or someone who cannot listen well can use subtitles to understand a video. Also, a person who has a low vision can use a screen reader to listen what is written on the screen [24]. Therefore, Web accessibility means that people with disabilities can use the Web without any type of barriers [24]. There are several standards related to accessibility that provide guidelines and recommendations [25]. Some of the most important, according to the International Organization for Standardization (ISO), are the following ones:

  • ISO 9241: covers ergonomics of human-computer interaction.

  • ISO 14915 (software ergonomics for multimedia user interfaces): multimedia controls and navigation structure.

  • ISO CD 9241-151 (software ergonomics for World Wide Web user interfaces): designs of Web user interfaces.

  • ISO TS 16071 (guidance on accessibility for human-computer interface): recommendations for the design of systems and software applications that allows a greater accessibility to computer systems for users with disabilities.

  • ISO CD 9241-20: accessibility guideline for information communication, equipment and services.

The Web Accessibility Initiative (WAI) [26] from the World Wide Web Consortium (W3C) [27] develops Web Content Accessibility Guidelines (WCAG) [28] 2.0 (at present 2.1) that covers a wide range of recommendations for making Web contents more accessible. These guidelines were considered a standard in 2012, the ISO/IEC 40500. Complementary to these guidelines are the W3C User Agent Accessibility guidelines [29] (UAAG) and Authoring tool Accessibility guidelines [30] (ATAG), which addresses the current technological capabilities to modify the presentation based on the device capabilities and the preferences of the user.

The World Wide Web Consortium (W3C) provides international standards to make the Web as accessible as possible. It comprises the Web 2.0 Content Accessibility Guidelines (WCAG 2.0) [31], also known as the ISO 40500 [32], which are adapted to the European Standard called EN 301549 [33].

The current version of the accessibility guidelines is “Web Content Accessibility Guidelines 2.1” (WCAG 2.1) [23]. WCAG 2.1 consists of 4 principles, 13 guidelines and 76 compliance criteria. The four principles refer to [34].

Principle 1—perceptibility: refers to the good practices regarding the presentation of information and user interface components. It consists of 4 guidelines and 29 compliance criteria.

Principle 2—operability: the components of the user interface and navigation must be operable. It includes 5 guidelines and 29 compliance criteria.

Principle 3—comprehensibility: the information and user interface management must be understandable. It has 3 guidelines and 17 compliance criteria.

Principle 4—robustness: the content must be robust enough to rely on the interpretation of a wide variety of user agents, including assistive technologies. It includes a guideline and three compliance criteria.

Usability and accessibility can be combined to achieve the development of more accessible, efficient, equitable and universal tele-rehabilitation systems. This chapter presents a systematic literature review of summative and formative usability studies as well as accessibility studies in the context of tele-rehabilitation systems. The remaining of the manuscript is composed of four sections. Section 2 presents the method used to proceed with the systematic review. Section 3 is a description of the most relevant papers in usability applied to tele-rehabilitation. Section 4 describes the results regarding the accessibility. And Section 5 draws conclusions on the main findings of this literature review.[…]


Continue —> A Systematic Review of Usability and Accessibility in Tele-Rehabilitation Systems | IntechOpen

Figure 1.
PRISMA 2009 flow diagram chart that shows the selection process of the papers included in the literature review for usability.

, , , ,

Leave a comment

[Abstract + References] Virtual System Using Haptic Device for Real-Time Tele-Rehabilitation of Upper Limbs


This paper proposes a tool to support the rehabilitation of upper limbs assisted remotely, which makes it possible for the physiotherapist to be able to assist and supervise the therapy to patients who can not go to rehabilitation centers. This virtual system for real-time tele-rehabilitation is non-invasive and focuses on involving the patient with mild or moderate mobility alterations within a dynamic therapy based on virtual games; Haptics Devices are used to reeducate and stimulate the movement of the upper extremities, at the same time that both motor skills and Visual-Motor Integration skills are developed. The system contains a virtual interface that emulates real-world environments and activities. The functionality of the Novint Falcon device is exploited to send a feedback response that corrects and stimulates the patient to perform the therapy session correctly. In addition, the therapy session can vary in intensity through the levels presented by the application, and the amount of time, successes and mistakes made by the patient are registered in a database. The first results show the acceptance of the virtual system designed for real-time tele-rehabilitation.


  1. 1.
    Ingram, T.T.S.: A historical review of the definition of cerebral palsy, the epidemiology of the cerebral palsies. In: Stanley, F.A.E. (ed.) The Epidemiology of the Cerebral Palsies, pp. 1–11. Lippincott, Philadelphia (1984)Google Scholar
  2. 2.
    Jones, M.W., Morgan, E., Shelton, J.E., Thorogood, C.: Cerebral palsy: introduction and diagnosis (part I). J. Pediatr. Health Care 21(3), 146–152 (2007)CrossRefGoogle Scholar
  3. 3.
    Aicardi, J.: Disease of the Nervous System in Childhood. MacKeith Press, London (1992)Google Scholar
  4. 4.
    Feldman, H.M., Chaves-Gnecco, D., Hofkosh, D.: Developmental-behavioral pediatrics. In: Zitelli, B.J., McIntire, S.C., Norwalk, A.J. (eds.) Atlas of Pediatric Diagnosis, Chap. 3, 6th edn. Elsevier Saunders, Philadelphia (2012)Google Scholar
  5. 5.
    Ketelaar, M., Vermeer, A., Hart, H., et al.: Effects of a functional therapy program on motor abilities of children with cerebral palsy. Phys. Ther. 81, 1534–1545 (2001)CrossRefGoogle Scholar
  6. 6.
    Taub, E., Ramey, S., DeLuca, S., Echols, K.: Efficacy of constraint-induced movement therapy for children with cerebral palsy with asymmetric motor impairment. Pediatrics 113, 305–312 (2004)CrossRefGoogle Scholar
  7. 7.
    Sakzewski, L., Ziviani, J., Boyd, R.N.: Efficacy of upper limb therapies for unilateral cerebral palsy: a meta-analysis. Pediatrics 133(1), e175–e204 (2014)CrossRefGoogle Scholar
  8. 8.
    Galil, A., Carmel, S., Lubetzky, H., Heiman, N.: Compliance with home rehabilitation therapy by parents of children with disabilities in Jews and Bedouin in Israel. Dev. Med. Child Neurol. 43(4), 261–268 (2001)CrossRefGoogle Scholar
  9. 9.
    De Campos, A.C., da Costa, C.S., Rocha, N.A.: Measuring changes in functional mobility in children with mild cerebral palsy. Dev. Neurorehabil. 14, 140–144 (2011)CrossRefGoogle Scholar
  10. 10.
    Prosser, L.A., Lee, S.C., Barbe, M.F., VanSant, A.F., Lauer, R.T.: Trunk and hip muscle activity in early walkers with and without cerebral palsy – a frequency analysis. J. Electromyogr. Kinesiol. 20, 851–859 (2010)CrossRefGoogle Scholar
  11. 11.
    Weiss, P.L.T., Tirosh, E., Fehlings, D.: Role of virtual reality for cerebral palsy management. J. Child Neurol. 29(8), 1119–1124 (2014). 0883073814533007CrossRefGoogle Scholar
  12. 12.
    Mitchell, L., Ziviani, J., Oftedal, S., Boyd, R.: The effect of virtual reality interventions on physical activity in children and adolescents with early brain injuries including cerebral palsy. Dev. Med. Child Neurol. 54, 667–671 (2012)CrossRefGoogle Scholar
  13. 13.
    Snider, L., Majnemer, A., Darsaklis, V.: Virtual reality as a therapeutic modality for children with cerebral palsy. Dev. Neurorehabil. 13, 120–128 (2010)CrossRefGoogle Scholar
  14. 14.
    Chen, Y.P., Lee, S.Y., Howard, A.M.: Effect of virtual reality on upper extremity function in children with cerebral palsy: a meta-analysis. Pediatric Phys. Therapy 26(3), 289–300 (2014)CrossRefGoogle Scholar
  15. 15.
    Golomb, M.R., McDonald, B.C., Warden, S.J., Yonkman, J., Saykin, A.J., Shirley, B., et al.: In-home virtual reality videogame telerehabilitation in adolescents with hemiplegic cerebral palsy. Arch. Phys. Med. Rehabil. 91, 1–8 (2010)CrossRefGoogle Scholar
  16. 16.
    Shin, J., Song, G., Hwangbo, G.: Effects of conventional neurological treatment and a virtual reality training program on eye-hand coordination in children with cerebral palsy. J. Phys. Therapy Sci. 27(7), 2151–2154 (2015). Scholar
  17. 17.
    Chen, Y.P., Kang, L.J., Chuang, T.Y., Doong, J.L., Lee, S.J., Tsai, M.W., Sung, W.H.: Use of virtual reality to improve upper-extremity control in children with cerebral palsy: a single-subject design. Phys. Therapy 87(11), 1441–1457 (2007)CrossRefGoogle Scholar
  18. 18.
    Bortone, I., Leonardis, D., Solazzi, M., Procopio, C., Crecchi, A., Bonfiglio, L., Frisoli, A.: Integration of serious games and wearable haptic interfaces for Neuro Rehabilitation of children with movement disorders: a feasibility study. In: 2017 International Conference on Rehabilitation Robotics (ICORR), pp. 1094–1099. IEEE, July 2017Google Scholar
  19. 19.
    Gupta, A., O’Malley, M.K.: Design of a haptic arm exoskeleton for training and rehabilitation. IEEE/ASME Trans. Mechatron. 11(3), 280–289 (2006)CrossRefGoogle Scholar
  20. 20.
    Kozhaeva, T., Zhestkov, S., Bulakh, D., Houlden, N.: Programmable gesture manipulator for hand injuries rehabilitation. In: Internet Technologies and Applications (ITA), pp. 134–136. IEEE, September 2017Google Scholar
  21. 21.
    Pruna, E., et al.: 3D virtual system using a haptic device for fine motor rehabilitation. In: Rocha, Á., Correia, A.M., Adeli, H., Reis, L.P., Costanzo, S. (eds.) WorldCIST 2017. AISC, vol. 570, pp. 648–656. Springer, Cham (2017). Scholar
  22. 22.
    Bortone, I., Leonardis, D., Solazzi, M., Procopio, C., Crecchi, A., Briscese, L., Andre, P., Bonfiglio, L., Frisoli, A.: Serious game and wearable haptic devices for neuro motor rehabilitation of children with cerebral palsy. In: Converging Clinical and Engineering Research on Neurorehabilitation II, pp. 443–447. Springer, Cham (2017). Scholar
  23. 23.
    Khor, K.X., Chin, P.J.H., Hisyam, A.R., Yeong, C.F., Narayanan, A.L.T., Su, E.L.M.: Development of CR2-Haptic: a compact and portable rehabilitation robot for wrist and forearm training. In: IEEEIECBES International Conference on Biomedical Engineering and Sciences, pp. 424–429 (2014)Google Scholar
  24. 24.
    Maciejasz, P., Eschweiler, J., Gerlach-Hahn, K., Jansen-Troy, A., Leonhardt, S.: A survey on robotic devices for upper limb rehabilitation. J. Neuroeng. Rehabil. 11, 3 (2014)CrossRefGoogle Scholar
  25. 25.
    Lum, P.S., Burgar, C.G., Shor, P.C., Majmundar, M., Van der Loos, M.: Robot-assisted movement training compared with conventional therapy techniques for the rehabilitation of upper-limb motor function after stroke. Arch. Phys. Med. Rehabil. 83, 952–959 (2002)CrossRefGoogle Scholar

via Virtual System Using Haptic Device for Real-Time Tele-Rehabilitation of Upper Limbs | SpringerLink

, , , , , , , ,

Leave a comment

[Abstract + References] Upper-Limb Tele-Rehabilitation System with Force Sensorless Dynamic Gravity Compensation


Tele-rehabilitation provides remote physiotherapy services for patients who have limited access to hospitals. This paper proposes a sensorless tele-rehabilitation system for the upper-limb using two robots in master–slave configuration. The system provides a transparent haptic feeling between the therapist and the patient by simultaneous tracking of both position and torque. The torque is measured using the reaction torque observer. Furthermore, an online recursive numerical parameter estimation method is proposed to identify the gravity disturbance in bilateral teleoperation. The system automatically estimates the parameters using the reaction torque observer output’s data while the therapist is delivering remote physiotherapy services. The estimated gravity torque is compensated in the system as an improvement of the transparency of the teleoperated system. Therefore the therapist would feel only the abnormalities of the patient’s arm. Estimated parameters automatically update the system and enhance the performance. The proposed method was practically verified with a master slave tele-rehabilitation system. Results suggest the applicability of the proposed method.


  1. 1.
    Plautz EJ, Milliken GW, Nudo RJ (2000) Effects of repetitive motor training on movement representations in adult squirrel monkeys: role of use versus learning. Neurobiol Learn Mem 74(1):27CrossRefGoogle Scholar
  2. 2.
    Stucki G, Stier-Jarmer M, Grill E, Melvin J (2005) Rationale and principles of early rehabilitation care after an acute injury or illness. Disabil Rehabil 27(7–8):353CrossRefGoogle Scholar
  3. 3.
    Babaiasl M, Mahdioun SH, Jaryani P, Yazdani M (2016) A review of technological and clinical aspects of robot-aided rehabilitation of upper-extremity after stroke. Disabil Rehabil Assist Technol 11(4):263Google Scholar
  4. 4.
    Prange GB, Jannink MJ, Groothuis-Oudshoorn CG, Hermens HJ, IJzerman MJ (2006) Systematic review of the effect of robot-aided therapy on recovery of the hemiparetic arm after stroke. J Rehabil Res Dev 43(2):171CrossRefGoogle Scholar
  5. 5.
    Volpe B, Krebs H, Hogan N, Edelstein L, Diels C, Aisen M (2000) A novel approach to stroke rehabilitation robot-aided sensorimotor stimulation. Neurology 54(10):1938CrossRefGoogle Scholar
  6. 6.
    Cherry CO, Chumbler NR, Richards K, Huff A, Wu D, Tilghman LM, Butler A (2017) Expanding stroke telerehabilitation services to rural veterans: a qualitative study on patient experiences using the robotic stroke therapy delivery and monitoring system program. Disabil Rehabil Assist Technol 12(1):21CrossRefGoogle Scholar
  7. 7.
    Zhang S, Guo S, Gao B, Hirata H, Ishihara H (2015) Design of a novel telerehabilitation system with a force-sensing mechanism. Sensors 15(5):11511CrossRefGoogle Scholar
  8. 8.
    Park HS, Peng Q, Zhang LQ (2008) A portable telerehabilitation system for remote evaluations of impaired elbows in neurological disorders. IEEE Trans Neural Syst Rehabil Eng 16(3):245CrossRefGoogle Scholar
  9. 9.
    Song A, Wu C, Ni D, Li H, Qin H (2016) One-therapist to three-patient telerehabilitation robot system for the upper limb after stroke. Int J Soc Robot 8(2):319CrossRefGoogle Scholar
  10. 10.
    Song A, Pan L, Xu G, Li H (2015) Adaptive motion control of arm rehabilitation robot based on impedance identification. Robotica 33(9):1795CrossRefGoogle Scholar
  11. 11.
    Just F, Özen Ö, Tortora S, Riener R, Rauter G (2017) Feedforward model based arm weight compensation with the rehabilitation robot ARMin. In: Rehabilitation robotics (ICORR), 2017 international conference on, IEEE, pp 72–77Google Scholar
  12. 12.
    Moubarak S, Pham MT, Moreau R, Redarce T (2010) Gravity compensation of an upper extremity exoskeleton. In: Engineering in medicine and biology society (EMBC), 2010 annual international conference of the IEEE, IEEE, pp 4489–4493Google Scholar
  13. 13.
    Ugurlu B, Nishimura M, Hyodo K, Kawanishi M, Narikiyo T (2015) Proof of concept for robot-aided upper limb rehabilitation using disturbance observers. IEEE Trans Hum Mach Syst 45(1):110CrossRefGoogle Scholar
  14. 14.
    Abeykoon AHS, Ruwanthika RM (2016) Remote gripping for effective bilateral teleoperation. In: Handbook of research on human–computer interfaces, developments, and applications, IGI Global, pp 99–134Google Scholar
  15. 15.
    Takei T, Shimono T, Kubo R, Nishi H, Ohnishi K (2008) Gravity compensation for improvement of operationarity in bilateral teleoperation. IEEJ Trans Ind Appl 128(6):767–774CrossRefGoogle Scholar
  16. 16.
    Nishimura K, Ohnishi K (2006) Gravity estimation and compensation of grasped object for bilateral teleoperation. In: Advanced motion control, 2006. 9th IEEE international workshop on, IEEE, pp 72–77Google Scholar
  17. 17.
    El Kalam AA, Ferreira A, Kratz F (2016) Bilateral teleoperation system using QoS and secure communication networks for telemedicine applications. IEEE Syst J 10(2):709CrossRefGoogle Scholar
  18. 18.
    Just F, Baur K, Riener R, Klamroth-Marganska V, Rauter G (2016) Online adaptive compensation of the ARMin Rehabilitation Robot. In: Biomedical robotics and biomechatronics (BioRob), 2016 6th IEEE international conference on, IEEE, pp 747–752Google Scholar
  19. 19.
    Katsura S, Matsumoto Y, Ohnishi K (2007) Modeling of force sensing and validation of disturbance observer for force control. IEEE Trans Ind Electron 54(1):530CrossRefGoogle Scholar
  20. 20.
    Mizuochi M, Tsuji T, Ohnishi K (2006) Improvement of disturbance suppression based on disturbance observer. In: 9th IEEE international workshop on advanced motion control, 2006, IEEE, pp 229–234Google Scholar
  21. 21.
    Perera GA, Pillai MB, Harsha A, Abeykoon S (2014) DC motor inertia estimation for robust bilateral control. In: Information and automation for sustainability (ICIAfS), 2014 7th international conference on, IEEE, pp 1–7Google Scholar
  22. 22.
    Ohnishi K, Matsui N, Hori Y (1994) Estimation, identification, and sensorless control in motion control system. Proc IEEE 82(8):1253CrossRefGoogle Scholar
  23. 23.
    Chinthaka MD, Abeykoon AHS (2015) Friction compensation of DC motors for precise motion control using disturbance observer. ECTI Trans Comput Inf Technol (ECTI-CIT) 9(1):74Google Scholar
  24. 24.
    Ohnishi K, Shibata M, Murakami T (1996) Motion control for advanced mechatronics. IEEE/ASME Trans Mechatron 1(1):56CrossRefGoogle Scholar

via Upper-Limb Tele-Rehabilitation System with Force Sensorless Dynamic Gravity Compensation | SpringerLink

, , , , , , , , ,

Leave a comment

[Abstract] Acceptance of Tele-Rehabilitation by Stroke Patients: Perceived Barriers and Facilitators



To explore the perceived barriers and facilitators of tele-rehabilitation (TR) by stroke patients, caregivers and rehabilitation therapists in an Asian setting.


Qualitative study involving semi-structured in-depth interviews and focus group discussions.


General community.


Participants (N=37) including stroke patients, their caregivers, and tele-therapists selected by purposive sampling.


Singapore Tele-technology Aided Rehabilitation in Stroke trial.

Main Outcome Measures

Perceived barriers and facilitators for TR uptake, as reported by patients, their caregivers, and tele-therapists.


Thematic analysis was used to inductively identify the following themes: facilitators identified by patients were affordability and accessibility; by tele-therapists, was filling a service gap and common to both was unexpected benefits such as detection of uncontrolled hypertension. Barriers identified by patients were equipment setup–related difficulties and limited scope of exercises; barriers identified by tele-therapists were patient assessments, interface problems and limited scope of exercises; and common to both were connectivity barriers. Patient characteristics like age, stroke severity, caregiver support, and cultural influence modified patient perceptions and choice of rehabilitation.


Patient attributes and context are significant determinants in adoption and compliance of stroke patients to technology driven interventions like TR. Policy recommendations from our work are inclusion of introductory videos in TR programs, provision of technical support to older patients, longer FaceTime sessions as re-enforcement for severely disabled stroke patients, and training of tele-therapists in assessment methods suitable for virtual platforms.

via Acceptance of Tele-Rehabilitation by Stroke Patients: Perceived Barriers and Facilitators – Archives of Physical Medicine and Rehabilitation

, , , , , , ,

Leave a comment

[SHORT ARTICLE] Tele rehabilitation: two-year experience in conducting medical assessments via tele link

by Nalinda Andraweera, Consultant Physician in Rehabilitation Medicine,
Modbury Public Hospital, Adelaide, Australia.


Telemedicine has been practised for many
decades since initial documentation in 1940s when
radiology images were sent between two townships
in Pennsylvania via telephone lines. Bioinstrumentation and transmission of astronauts’ vital parameters to ground based flight surgeons came to
forefront during NASA’s space programme in 1960s.
During following decades, telemedicine was used in
multiple medical specialties as a mode of patient
assessment. Use of telemedicine in Rehabilitation
Medicine is relatively recent. As multidisciplinary
coordinated care led by rehabilitation physicians and
allied clinicians is required, proformas are used in
tele rehabilitation assessments. Proformas help to
generate a clinical document with medical and allied
health assessments in one clinical record. Currently,
delivery of rehabilitation services is further empowered, enhanced and in evolution with the installation of dedicated software programmes for use by
allied health clinicians. Most units operating tele
medicine for rehabilitation medical services use
trained proctor with the client/patient to enable
more comprehensive examination to aid clinical
decision when the physician is stationed in a distant


Current evidence based on multi centre trials
suggest that well conducted tele rehabilitation enable
clinical outcomes similar to face to face rehabilitation.
Advantages of tele rehabilitation being low cost and
the ability to provide an increased volume of therapy
[1]. Drawbacks include limitations in detailed examination and negative implications in rehabilitation goal setting. If patients are reviewed early, frequent
and active communication is carried out during tele
rehabilitation, patient centred goal setting can be
improved [2].


Client assessments were from a city Hospital in
Adelaide (Modbury Hospital) linked via a video link
to a regional general hospital (Riverland General
Hospital in Berri) 241 kilometres from Adelaide.
Period assessed is from May 2016 to September 2018.
Fortnightly tele ward rounds and additional initial
inpatient and outpatient assessments were conducted via a video link. Both inpatient and outpatientclients were informed and educated about method of
tele medicine and tele rehabilitation and consent was
obtained for video-based assessments with the
physician. A trained proctor was present at each
Tele rehabilitation services were provided using
a secure, encrypted platform with privacy and
confidentiality maintained. Video link was established via a licenced communication provider enabling an uninterrupted video connection linking
patient and proctor with the physician. Electronic
transfer of clinical records was done using a secure
health email platform.
Trained proctor was a clinical nurse practitioner,
physiotherapist or an occupational therapist trained
to aid in clinical examinations required for musculoskeletal and neurological examination. Proformas were emailed to the physician prior to patient
assessment with medical history, current vital
parameters, medications and initial allied health
assessments. Video based clinical assessments were
recorded in a client proforma and a clinical report
was generated. Radiology and haematology/
biochemistry investigations were reviewed using a
medial investigation software used in South
Australian Health Service (Oasis). Urgent images
requested by the physician were done locally or at a
private service provider and snip tooled using a
licenced health imaging access pathway. Allied
health clinicians recorded initial functional levels
using FIM (Functional Independent Measure).
Following patient assessment, patient centred
realistic goals were discussed with the patient and
the multi-disciplinary team via video link.


Assessments done from 18 May 2016 to 17
September 2018 were assessed. A total of 236 Tele
medicine assessments were completed for patients/
clients admitted for rehabilitation. Average duration
for an assessment was 26 minutes. Patient satisfaction
on telemedicine assessments was 100%.


Tele medical assessments of patients admitted
for rehabilitation is currently gaining momentum and
more health funding is allocated for further expansion
of tele medicine and tele rehabilitation. Carrying out
medical assessments via a licenced video linkage
allows clients/patients to be reviewed with minimal
delay, closer to their homes and without the need to
travel to a specialist centre in a city. Tele medical
assessments save time for physicians as no travel time
is required, objective assessments can be done
effectively with the help of a trained proctor. Assessment reports can be generated with minimal delay using proformas and electronically transferred to
local GPs and multidisciplinary rehabilitation team
members comprising physiotherapists, occupational
therapists, nurse practitioners, social workers and
nutritionists/dieticians. Tele medical assessments in
rehabilitation aid uninterrupted rehabilitation service
provision in a distant site. Patient satisfaction is high.


  1. O’Neil O, Fernandez MM, Herzog J, Beorchia M, Gower V,
    Gramatica F, et al. Virtual Reality for Neurorehabilitation:
    Insights From 3 European Clinics. PM R. 2018; 10(9S2):
  2. Plant SE, Tyson SF, Kirk S, Parsons J. What are the barriers
    and facilitators to goal-setting during rehabilitation for
    stroke and other acquired brain injuries? A systematic
    review and meta-synthesis. Clin Rehabil. 2016; 30(9):

, , , , ,

Leave a comment

[WEB SITE] HOMEREHAB – Development of Robotic Technology for Post-Stroke Home Tele-Rehabilitation – The European Coordination Hub for Open Robotics Development


Rehabilitation can help hemiparetic patients to learn new ways of using and moving their weak arms and legs. With immediate therapy it is also possible that people who suffer from hemiparesis may eventually regain movement. However, reductions in healthcare reimbursement place constant demands on rehabilitation specialists to reduce the cost of care and improve productivity. Service providers have responded by shortening the length of patient hospitalisation.

The HOMEREHAB project will develop a new tele-rehabilitation robotic system for delivering therapy to stroke patients at home. It will research on the complex trade-off between robotic design requirements for in home systems and the performance required for optimal rehabilitation therapies, which current commercial systems designed for laboratories and hospitals do not take into account. Additionally, the new home scenario also demands for the smart monitoring of the patient’s physiological state, and the adaptation of the rehabilitation therapy for an optimal service.



Universidad Miguel Hernández de Elche (UMH)
Nicolas M. Garcia-Aracil


CEIT – Centro de Estudios e Investigaciones Técnicas
Iñaki Díaz


Instead Technologies
Alejandro García Moll







via HOMEREHAB – Development of Robotic Technology for Post-Stroke Home Tele-Rehabilitation – The European Coordination Hub for Open Robotics Development

, , , , , ,

Leave a comment

%d bloggers like this: