A decision-theoretic approach in the design of an adaptive upper-limb stroke rehabilitation robot

Huq, Rajibul; Kan, Patricia; Goetschalckx, Robby; Hébert, Debbie; Hoey, Jesse; Mihailidis, Alex

doi:10.1109/icorr.2011.5975418

Cited by 7 publications

(2 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The system consists of a haptic robotic device coupled to a POMDP model that tracks a user's progress over time, and adjusts the level of difficulty based on the user's current abilities. More details on this system can be found in Kan et al [2008Kan et al [ , 2011, Lam et al [2008], Huq et al [2011], and Goetschalckx et al [2011].…”

Section: Stroke Rehabilitation: Istretchmentioning

confidence: 97%

People, sensors, decisions

Hoey

Boutilier

Poupart

et al. 2012

ACM Trans. Interact. Intell. Syst.

View full text Add to dashboard Cite

The ratio of healthcare professionals to care recipients is dropping at an alarming rate, particularly for the older population. It is estimated that the number of persons with Alzheimer's disease, for example, will top 100 million worldwide by the year 2050 [Alzheimer's Disease International 2009]. It will become harder and harder to provide needed health services to this population of older adults. Further, patients are becoming more aware and involved in their own healthcare decisions. This is creating a void in which technology has an increasingly important role to play as a tool to connect providers with recipients. Examples of interactive technologies range from telecare for remote regions to computer games promoting fitness in the home. Currently, such technologies are developed for specific applications and are difficult to modify to suit individual user needs. The future potential economic and social impact of technology in the healthcare field therefore lies in our ability to make intelligent devices that are customizable by healthcare professionals and their clients, that are adaptive to users over time, and that generalize across tasks and environments.A wide application area for technology in healthcare is for assistance and monitoring in the home. As the population ages, it becomes increasingly dependent on chronic healthcare, such as assistance for tasks of everyday life (washing, cooking, dressing), medication taking, nutrition, and fitness. This article will present a summary of work over the past decade on the development of intelligent systems that provide assistance to persons with cognitive disabilities. These systems are unique in that they are all built using a common framework, a decision-theoretic model for general-purpose assistance in the home. In this article, we will show how this type of general model can be applied to a range of assistance tasks, including prompting for activities of daily living, assistance for art therapists, and stroke rehabilitation. This model is a Partially Observable Markov Decision Process (POMDP) that can be customized by end-users, that can integrate complex sensor information, and that can adapt over time. These three characteristics of the POMDP model will allow for increasing uptake and long-term efficiency and robustness of technology for assistance.

show abstract

Section: Stroke Rehabilitation: Istretchmentioning

confidence: 97%

People, sensors, decisions

Hoey

Boutilier

Poupart

et al. 2012

ACM Trans. Interact. Intell. Syst.

View full text Add to dashboard Cite

show abstract

“…For instance, Pehlivan et al designed a minimal assist-as-needed (mAAN) controller, which uses a model-based sensorless force estimation method to determine subject capability and provide required minimal assist-as-needed rehabilitation [12]. Huq et al designed the partially observable Markov decision process (POMDP), which allows an automated rehabilitation system to autonomously adjust different exercise parameters according to each individual's needs [13]. Artificial intelligence (AI) methods such as artificial neural networks [14] have also been employed for improving the intelligence when performing active assistance to a user's affected arm.…”

Section: Introductionmentioning

confidence: 99%

A Telepresence System for Therapist-in-the-Loop Training for Elbow Joint Rehabilitation

Zhang

Guo

et al. 2019

Applied Sciences

View full text Add to dashboard Cite

This paper proposes a new robotic rehabilitation training platform that is motivated by the requirement for adjusting the training strategy and intensity in a patient-specific manner. The platform is implemented for tele-rehabilitation and is comprised of a haptic device operated by therapists, a lightweight exoskeleton worn by patients and a visually shared model. Through the visually shared model, the motion of the therapist and patient are measured and mapped to the motion of the corresponding object. Thus, the force generated by the therapist can be transferred to the patient for delivering training, while real-time force feedback with high transparency can be provided to the therapist so they know the amount of force being applied to patients in real time. In particular, both assistive therapy in the early stages and resistive therapy in the later stages of stroke can be performed. The home-use exoskeleton device is specifically designed to be light-weight and compliant for safety. The patient-exoskeleton and therapist-haptic interaction performance is evaluated by observing the muscle activities and interaction force. Two volunteers were requested to imitate the process of the therapist-in-the-loop training to evaluate the proposed platform.

show abstract

An exploration of physiotherapists’ experiences of robotic therapy in upper limb rehabilitation within a stroke rehabilitation centre

Stephenson

Stephens

2017

Disability and Rehabilitation: Assistive Technology

View full text Add to dashboard Cite

RT was perceived positively by physiotherapists, regarded as an adjunct to conventional therapy. A framework to summarize the relationships of participants' views and experiences is proposed in an attempt to understand the influences on the clinical use of RT. Implications for Rehabilitation Robotic therapy (RT) is valued as an adjunct to (conventional) person-centred rehabilitation. Resource management and skill mix are viewed as two key challenges to the successful implementation of RT. The production of evidence-based guidelines would be a useful development in the advancement.

show abstract

A decision-theoretic approach in the design of an adaptive upper-limb stroke rehabilitation robot

Cited by 7 publications

References 14 publications

People, sensors, decisions

People, sensors, decisions

A Telepresence System for Therapist-in-the-Loop Training for Elbow Joint Rehabilitation

An exploration of physiotherapists’ experiences of robotic therapy in upper limb rehabilitation within a stroke rehabilitation centre

Contact Info

Product

Resources

About