Posts Tagged motor rehabilitation
[Abstract+References] Architectural Design of a Cloud Robotic System for Upper-Limb Rehabilitation with Multimodal Interaction
The rise in the cases of motor impairing illnesses demands the research for improvements in rehabilitation therapy. Due to the current situation that the service of the professional therapists cannot meet the need of the motor-impaired subjects, a cloud robotic system is proposed to provide an Internet-based process for upper-limb rehabilitation with multimodal interaction.
In this system, therapists and subjects are connected through the Internet using client/server architecture. At the client site, gradual virtual games are introduced so that the subjects can control and interact with virtual objects through the interaction devices such as robot arms. Computer graphics show the geometric results and interaction haptic/force is fed back during exercising. Both video/audio information and kinematical/physiological data are transferred to the therapist for monitoring and analysis.
In this way, patients can be diagnosed and directed and therapists can manage therapy sessions remotely. The rehabilitation process can be monitored through the Internet. Expert libraries on the central server can serve as a supervisor and give advice based on the training data and the physiological data. The proposed solution is a convenient application that has several features taking advantage of the extensive technological utilization in the area of physical rehabilitation and multimodal interaction.
[Thesis] Ubiquitous and Wearable Computing Solutions for Enhancing Motor Rehabilitation of the Upper Extremity Post-Stroke
Coffey, Aodhan L. (2016) Ubiquitous and Wearable Computing Solutions for Enhancing Motor Rehabilitation of the Upper Extremity Post-Stroke. PhD thesis, National University of Ireland Maynooth.
A stroke is the loss of brain function caused by a sudden interruption in the blood supply of the brain. The extent of damage caused by a stroke is dependent on many factors such as the type of stroke, its location in the brain, the extent of oxygen deprivation and the criticality of the neural systems affected. While stroke is a non-cumulative disease, it is nevertheless a deadly pervasive disease and one of the leading causes of death and disability worldwide. Those fortunate enough to survive stroke are often left with some form of serious long-term disability. Weakness or paralysis on one side of the body, or in an individual limb is common after stroke. This affects independence and can greatly limit quality of life.
Stroke rehabilitation represents the collective effort to heal the body following stroke and to return the survivor to as normal a life as possible. It is well established that rehabilitation therapy comprising task-specific, repetitive, prolonged movement training with learning is an effective method of provoking the necessary neuroplastic changes required which ultimately lead to the recovery of function after stroke. However, traditional means of delivering such treatments are labour intensive and constitute a significant burden for the therapist limiting their ability to treat multiple patients. This makes rehabilitation medicine a costly endeavour that may benefit from technological contributions. As such, stroke has severe social and economic implications, problems exasperated by its age related dependencies and the rapid ageing of our world. Consequently these factors are leading to a rise in the number living with stroke related complications. This is increasing the demand for post stroke rehabilitation services and places an overwhelming amount of additional stress on our already stretched healthcare systems.
Therefore, new innovative solutions are urgently required to support the efforts of healthcare professionals in an attempt to alleviate this stress and to ultimately improve the quality of care for stroke survivors. Recent innovations in computer and communication technology have lead to a torrent of research into ubiquitous, pervasive and distributed technologies, which might be put to great use for rehabilitative purpose. Such technology has great potential utility to support the rehabilitation process through the delivery of complementary, relatively autonomous rehabilitation therapy, potentially in the comfort of the patient’s own home.
This thesis describes concerted work to improve the current state and future prospects of stroke rehabilitation, through investigations which explore the utility of wearable, ambient and ubiquitous computing solutions for the development of potentially transformative healthcare technology. Towards this goal, multiple different avenues of the rehabilitation process are explored, tackling the full chain of processes involved in motor recovery, from brain to extremities. Subsequently, a number of cost effective prototype devices for use in supporting the ongoing rehabilitation process were developed and tested with healthy subjects, a number of open problems were identified and highlighted, and tentative solutions for home-based rehabilitation were put forward. It is envisaged that the use of such technology will play a critical role in abating the current healthcare crisis and it is hoped that the ideas presented in this thesis will aid in the progression and development of cost effective, efficacious rehabilitation services, accessible and affordable to all in need.
[Stroke Rehabilitation Clinician Handbook] 4. Motor Rehabilitation – 4A. Lower Extremity and Mobility – Full Text PDF
4.1 Motor Recovery of the Lower Extremity Post Stroke
Factors that Predict Motor Recovery
Motor deficits post-stroke are the most obvious impairment (Langhorne et al. 2012) and have a disabling impact on valued activities and independence. Motor deficits are defined as “a loss or limitation of function in muscle control or movement or a limitation of movement” (Langhorne et al. 2012; Wade 1992). Given its importance, a large proportion of stroke rehabilitation efforts are directed towards the recovery of movement disorders. Langhorne et al. (2012) notes that motor recovery after stroke is complex with many treatments designed to promote recovery of motor impairment and function.
The two most important factors which predict motor recovery are:
- Stroke Severity: The most important predictive factor which reduces the capacity for brain reorganization.
- Age: Younger patients demonstrate greater neurological and functional recovery and hence have a better prognosis compared to older stroke patients (Adunsky et al. 1992; Hindfelt & Nilsson 1977; Marini et al. 2001; Nedeltchev et al. 2005).
Changes in walking ability and gait pattern often persist long-term and include increased tone, gait asymmetry, changes in muscle activation and reduced functional abilities (Wooley 2001; Robbins et al. 2006; Pizzi et al. 2007, Pereira et al. 2012). Ambulation post stroke is often less efficient and associated with increased energy expenditure (Pereira et al. 2012). Hemiplegic individuals have been reported to utilize 50-67% more metabolic energy that normal individuals when walking at the same velocity (Wooley et al. 2001).
For mobility outcome, trunk balance is an additional predictor of recovery (Veerbeek et al. 2011). Nonambulant patients who regained sitting balance and some voluntary movement of the hip, knee and/or ankle within the first 72 hours post stroke predicted 98% chance of regaining independent gait within 6 months. In contrast, those who were unable to sit independently for 30 seconds and could not contract the paretic lower limb within the first 72 hours post stroke had a 27% probability of achieving independent gait.
This single volume brings together both theoretical developments in the field of motor control and their translation into such fields as movement disorders, motor rehabilitation, robotics, prosthetics, brain-machine interface, and skill learning. Motor control has established itself as an area of scientific research characterized by a multi-disciplinary approach. Its goal is to promote cooperation and mutual understanding among researchers addressing different aspects of the complex phenomenon of motor coordination. Topics covered include recent theoretical advances from various fields, the neurophysiology of complex natural movements, the equilibrium-point hypothesis, motor learning of skilled behaviors, the effects of age, brain injury, or systemic disorders such as Parkinson’s Disease, and brain-computer interfaces.
In this issue of Cell Reports, Ossmy and Mukamel (2016) show that virtual reality enhances learning of new motor sequences through practice with one hand and synchronous feedback of the other hand moving. The approach holds promise for motor rehabilitation.
Everyday tasks require sequences of movements with one or both hands. For example, many times a day, you may use one hand to unzip your pocket, find your keys, and unlock your car. We take such practiced sequences for granted because they are so well practiced as to seem effortless. However, imagine that you have had a stroke and struggle to control one of your hands. In such cases, learning or relearning even simple motor sequences would be frustratingly difficult. You might be able to take advantage of the fact that motor learning shows some transfer between hands—learn the task with the good right hand and your problematic left hand may also benefit—but such effects are modest. But what if there were a way to boost your motor sequence learning with the help of virtual reality?
In this issue of Cell Reports, Ori Ossmy and Roy Mukamel at Tel-Aviv University show that virtual reality can help people learn movement sequences rapidly ( Ossmy and Mukamel, 2016). Healthy participants performed an arbitrary sequence of digit movements as rapidly as possible for 30 seconds with one hand and then with the other. Then they spent five minutes practicing the sequence with real movements of the right hand in a virtual reality setup. Finally, they repeated the test sequence with each hand (Figure 1).
Computer systems such as virtual environments and serious games are being used as a tool to enhance the process of user rehabilitation. These systems can help motivate and provide means to assess the user’s performance undertaking an exercise session. To do that, these systems incorporate motion tracking and gesture recognition devices, such as natural interaction devices like Kinect and Nintendo Wii. These devices, originally developed for the games market, allowed the development of low cost and minimally invasive rehabilitation systems, allowing the treatment to be taken to the patient’s residence. With the advent of natural interaction based on electromyography, devices that use electromyographic signals can also be used to construct these systems. The aim of this work is to show how electromyographic signals could be used as a tool to capture user gestures and incorporated into home-based rehabilitation systems by adopting a low-cost device to capture these gestures. The process of creation of a serious game to show some of these concepts is also present.
[Abstract] New Trends in the Use of Robotic Devices in Motor Rehabilitation of Upper Limbs – Springer
In the years to come, robotic systems assisting physical rehabilitation will be used mainly by elderly, disabled, as well as children and adults after accidents and disorders limiting their physical capabilities. As the population is getting older, the issue becomes more and more critical.
A growing number of people requiring rehabilitation generates significant costs, of which personal expenses are a major component. Providing the human personnel with appropriate mechatronic devices or replacing at least some rehabilitation medicine specialists with robots could reduce physical and mental workload of physicians. Broader application of such devices will also require among others new solutions in mechanic, control and human-robot communication.
This paper presents overall vision of the development of rehabilitation robots, with consideration of the observed trends in this area, as well as expected achievements in electronics, material’s engineering, ICT and other related fields of science and technology.
[CONFERENCE PAPER] Patient motivation in virtual environments for arm rehabilitation at home – Full Text PDF
Many technologies have been deployed for motor rehabilitation at home, but most patients do not comply with the exercise regimen due to lack of motivation. This can be addressed with virtual environments that engage and motivate the patient. We will therefore investigate different methods of increasing patient motivation during arm rehabilitation at home. As a first step, we will focus on virtual environments where patients can compete or cooperate with their caretakers in different gamelike tasks. Different games will be developed and augmented with difficulty adaptation methods, then tested in multisession studies to determine their effect on motivation. Later, we will also investigate other ways of motivating the patient as well as ways to train coordinated motion of both arms.
[ARTICLE] Motor Imagery based Brain-Computer Interfaces: An Emerging Technology to Rehabilitate Motor Deficits
- BCIs permit to reintegrate the sensory-motor loop by accessing to brain information.
- Motor imagery based BCIs seem to be an effective system for an early rehabilitation.
- This technology does not need remaining motor activity and promotes neuroplasticity.
- BCI for rehabilitation tends towards implantable devices plus stimulation systems.
When the sensory-motor integration system is malfunctioning provokes a wide variety of neurological disorders, which in many cases cannot be treated with conventional medication, or via existing therapeutic technology. A brain-computer interface (BCI) is a tool that permits to reintegrate the sensory-motor loop, accessing directly to brain information. A potential, promising and quite investigated application of BCI has been in the motor rehabilitation field. It is well-known that motor deficits are the major disability wherewith the worldwide population lives. Therefore, this paper aims to specify the foundation of motor rehabilitation BCIs, as well as to review the recent research conducted so far (specifically, from 2007 to date), in order to evaluate the suitability and reliability of this technology. Although BCI for post-stroke rehabilitation is still in its infancy, the tendency is towards the development of implantable devices that encompass a BCI module plus a stimulation system.
[ARTICLE] A novel method for the quantification of key components of manual dexterity after stroke – Full Text HTML
A high degree of manual dexterity is a central feature of the human upper limb. A rich interplay of sensory and motor components in the hand and fingers allows for independent control of fingers in terms of timing, kinematics and force. Stroke often leads to impaired hand function and decreased manual dexterity, limiting activities of daily living and impacting quality of life. Clinically, there is a lack of quantitative multi-dimensional measures of manual dexterity. We therefore developed the Finger Force Manipulandum (FFM), which allows quantification of key components of manual dexterity. The purpose of this study was (i) to test the feasibility of using the FFM to measure key components of manual dexterity in hemiparetic stroke patients, (ii) to compare differences in dexterity components between stroke patients and controls, and (iii) to describe individual profiles of dexterity components in stroke patients.
10 stroke patients with mild-to-moderate hemiparesis and 10 healthy subjects were recruited. Clinical measures of hand function included the Action Research Arm Test and the Moberg Pick-Up Test. Four FFM tasks were used: (1) Finger Force Tracking to measure force control, (2) Sequential Finger Tapping to measure the ability to perform motor sequences, (3) Single Finger Tapping to measure timing effects, and (4) Multi-Finger Tapping to measure the ability to selectively move fingers in specified combinations (independence of finger movements).
Most stroke patients could perform the tracking task, as well as the single and multi-finger tapping tasks. However, only four patients performed the sequence task. Patients showed less accurate force control, reduced tapping rate, and reduced independence of finger movements compared to controls. Unwanted (erroneous) finger taps and overflow to non-tapping fingers were increased in patients. Dexterity components were not systematically related among each other, resulting in individually different profiles of deficient dexterity. Some of the FFM measures correlated with clinical scores.
Quantifying some of the key components of manual dexterity with the FFM is feasible in moderately affected hemiparetic patients. The FFM can detect group differences and individual profiles of deficient dexterity. The FFM is a promising tool for the measurement of key components of manual dexterity after stroke and could allow improved targeting of motor rehabilitation.