Posts Tagged Medical treatment
Video games are constantly evolving and today they are one of the main types of entertainment. As we live in the digital age, the implementation of IT solutions in other areas of activity remains relevant. Today, almost all processes use IT technologies: calling a taxi, ordering food, education, shopping, and so on. The use of IT technologies in the field of medicine is not uncommon. But it’s not often that you see video games being used in this area. Video games and their development are an integral part of the IT sphere. The technologies that exist now allow us to create our own game products, which can then be implemented in other processes. This research is aimed at studying the term of “gamification”, its impact on rehabilitation processes, and the study of gamification tools and game products used in the field of medicine. In this research we propose a gamified solution for hand rehabilitation process which include 3D game that work in conjunction with the VR tool called Leap Motion. Since video games attract people with reward systems, goals and many other factors, why not to use it as a key element in process of rehabilitation? In some cases, it is more effective method rather than traditional therapy.
[Abstract + References] Automated Voluntary Finger Lifting Rehabilitation Support Device for Hemiplegic Patients to Use at Home
We have been proposing a robotic finger rehabilitation support device for hemiplegic patients that can be used at home. This device instructs a patient to lift a finger voluntarily and provides assistance when the patient is impossible to lift. In previous studies, we have shown an automated evaluation method which monitors the level of involuntary finger movement. However, the detailed procedure of finger rehabilitation has not been clarified. In this paper, we show a practical procedure of finger rehabilitation as well as a hardware design of the device. We also discuss safety issues during finger lift assistance. Our design limits the speed of finger lift so that it avoids unwanted contraction of finger muscles by stretch reflex. Also, the angle of finger lift is limited in our design so that it will not exceed the maximum excursion of an MP joint.
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Many people in the world are increasingly suffering from stroke issues. Survivors often tend to suffer from hemiplegia or related conditions, in which some portion of their body may be rendered useless. The wrist is one such part. But this injury can be recovered by conventional rehabilitation processes like physical therapy. In this paper, a device for robot-assisted physical therapy is presented for wrist rehabilitation. It can overcome the lack of availability of physical therapists and reduce the cost incurred in long-term therapy. Also, it can provide accurate regular exercises without missing any step even in the absence of the therapist. These two DOF robotic devices can learn the physical exercise (i.e. wrist-based movements) from the trained therapist through an electronic smart-band. It can also replicate these exercises when the patient wears this device over his/her wrist. Here, an accelerometer sensor and a magnetometer sensor-based smart-band are used for recognizing the wrist motions like flexion, extension, abduction, and adduction. The objective of this preliminary work is to drive accurately all the motor actuators which are attached to the robot and calibrate the feedback sensor to reflect the movement of the smart-band. In the future, this robot can be used as a teleoperated rehabilitation device through an IoT platform.
It is estimated that about 15 million people a year suffer from stroke worldwide, with 5 million stroke survivors experiencing permanent motor disability requiring therapeutic services. It has been shown that early involvement in rehabilitation therapies has a desirable effect on the long-term recovery of patients. There are, however, several challenges with the current state of delivering rehabilitation services, including limitations on the number of clinics, financial needs, and human resources. Robotic systems have been proposed in the literature to help with these challenges. However, most of the existing robotic systems are expensive, not-portable, and cannot be used for both upper-and lower-limb rehabilitation. This paper presents a 3-DOF robotic device that has been designed to deliver both upper-and lower-limb therapy and incorporates a novel mechanical safety mechanism. The device is capable of teleoperation which makes it particularly suitable for telerehabilitation in the current COVID-19 environment. The rehabilitation robot can deliver therapy in assistive and resistive modes to aid patients at all stages of recovery. In the assistive mode, the robot’s motion provides input to help the patient in completing the therapy task, while in the resistive mode, the robot opposes the motions generated by the patient thereby requiring additional muscle actuation. The robot has been tested by physiotherapists to assess its validity in a clinical setting, and by healthy participants to assess its functionality, safety, and engineering design. The study found that 80physiotherapists agreed the platform has the potential to improve patient outcomes.
[Abstract + References] A Virtual Reality Serious Game for Hand Rehabilitation Therapy – IEEE Conference Publication
The human hand is the body part most frequently injured in occupational accidents, accounting for one out of five emergency cases and often requiring surgery with subsequently long periods of rehabilitation. This paper proposes a Virtual Reality game to improve conventional physiotherapy in hand rehabilitation, focusing on resolving recurring limitations reported in most technological solutions to the problem, namely the limited diversity support of movements and exercises, complicated calibrations and exclusion of patients with open wounds or other disfigurements of the hand. The system was assessed by seven able-bodied participants using a semistructured interview targeting three evaluation categories: hardware usability, software usability and suggestions for improvement. A System Usability Score (SUS) of 84.3 and participants’ disposition to play the game confirm the potential of both the conceptual and technological approaches taken for the improvement of hand rehabilitation therapy.
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[Abstract + References] Iterative Learning Control of Gravity Compensation for Upper-Arm Robot-Assisted Rehabilitation
Robot-assisted rehabilitation allows patients e.g. suffering from a stroke to practice without continuous supervision from a therapist. To activate neuroplasticity, the patient has to actively participate in the rehabilitation therapy and the robot should only provide as much assistance as required based on the patient’s needs and abilities. For this purpose, gravity compensation is a promising approach as simplifying movements enables the patient to increase the training’s intensity and number of repetitions. Thus, the aim of this paper is the application and implementation of an iterative learning control scheme to adjust the gravity compensation during therapy based on the patient’s abilities. For this purpose, a norm-optimal iterative learning control scheme and an optimization-based proportional-type iterative learning control algorithm are used. To validate and compare them, an experiment with a linear and a second one with a circular motion trajectory is done, while a slowly changing repetitive disturbance in form of an artificial force is applied to imitate the patient. In this case, the measured number of samples per cycle differs due to the underlying control scheme of the robot. For this reason, a mapping process based on the Dijkstra method is done. The results illustrate that both algorithms are robust against disturbances and yield good tracking performance. Thus, also other factors such as the computation effort of both algorithms should be considered in future research.
[Conference Paper] HandMATE: Wearable Robotic Hand Exoskeleton and Integrated Android App for At Home Stroke Rehabilitation – Full Text
We have developed HandMATE (Hand Movement Assisting Therapy Exoskeleton); a wearable motorized hand exoskeleton for home-based movement therapy following stroke. Each finger and the thumb is powered by a linear actuator which provides flexion and extension assistance. Force sensitive resistors integrated into the design measure grasp and extension initiation force. An assistive therapy mode is based on an admittance control strategy. We evaluated our control system via subject and bench testing. Errors during a grip force tracking task while using the HandMATE were minimal (<1%) and comparable to unassisted healthy hand performance. We also outline a dedicated app we have developed for optimal use of HandMATE at home. The exoskeleton communicates wirelessly with an Android tablet which features guided exercises, therapeutic games and performance feedback. We surveyed 5 chronic stroke patients who used the HandMATE device to further evaluate our system, receiving positive feedback on the exoskeleton and integrated app.
Stroke is the leading cause of severe long-term disability in the US . The probability of regaining functional use of the impaired upper extremity is low . At 6 months post stroke, 62% of survivors failed to achieve some dexterity . Such impairments can inhibit the individual’s ability to perform activities of daily living (ADL). Subsequently, upper limb rehabilitation recovery to improve ADL is one of the main self-reported goals of stroke survivors .
Outpatient rehabilitation is recommended for survivors that have been discharged from inpatient rehabilitative services . However, outpatient rehabilitation in general is largely underutilized, with only 35.5% of stroke survivors using services . Factors inhibiting outpatient therapy include cost, lack of resources and transportation. Wearable robotics that enable home-based therapy have the potential to overcome these barriers. They provide assistive movement forces which enable task-specific training in real-life situations that patients are often unable to practice without a clinician. See  for wearable hand robots for rehabilitation review.
At home therapy is not without its limitations. The inability to motivate oneself and fatigue are the most common reported factors resulting in failure to adhere to home based exercise programs for stroke recovery . While wearable robotics can reduce fatigue during exercise, it does not directly address lack of motivation. Research has shown incorporating games into home therapy can encourage compliance . Zondervan et al. showed that use of an instrumented sensor glove, named the MusicGlove, improved self-reported use and quality of movement, greater than convention at home exercises . Other studies showed increased motivation to complete the therapeutic exercises and optimized movement when the user is given feedback of their performance via the Microsoft Kinect . Wearable robotic systems that offer feedback and gaming capability may optimize at home stroke therapy.
Such a system was presented by Nijenhuis et al. in which stroke survivors showed motor improvements after completing a 6 week self-administered training program comprised of a dynamic hand orthosis and gaming environment . However, the hand device was passive, assisting only with extension, which limits the range of stroke survivors who could utilize such a system. Research groups have proposed combining their powered take-home wearable hand devices with custom integrated gaming systems , or guided exercises ; however, they have yet to conduct clinical trials. Notably, Ghassemi et al., have developed an integrated multi-user VR system to use with their X-Glove actuated orthosis, which will allow for client-therapist sessions without the patient having to travel .
Tablets are relatively inexpensive, portable, and straight forward to use, with 47% of internet users globally already owning one . Furthermore, a recent study demonstrated the success of a tablet based at home exercise program in improving the recovery of stroke survivors . Notably, the study evaluated the accessibility of tablets, concluding every participant used the tablet successfully. Therefore a wearable powered hand robot with a dedicated tablet app which will provide functional games, task-specific guided exercises and feedback of movement, could optimize at home stroke therapy.
The goal of this project was to create a wearable robotic exoskeleton that enables repetitive practice of task-specific and goal orientated movements, which translates into improvements in ADL. Furthermore, for maximum use and successful integration into home-based rehabilitation, we aimed to create an Android application compatible with the robotic exoskeleton.
To meet these goals, the following design objectives were established: 1) Assistance with finger flex/extension. 2) Assistance with thumb carpometacarpal (CMC) add/abduction and thumb metacarpophalangeal (MCP) flex/extension. 3) Independent assistive control of each finger and thumb. 4) Portable for at home use, meaning the device has to be lightweight and wireless. 5) Relatively affordable. 6) Integrated with android tablet app. Specific design goals for the app included: 1) Easy to use. 2) Allow the user to control the exoskeletons assistance mode through the app. 3) Records the user’s data and prompts the user via notifications to complete the allocated daily or weekly recommended activity time.
In this paper we will evaluate if the proposed device and app goals have been achieved via bench and subject testing.
The HandMATE device (Fig. 1) builds upon the Hand Spring Operated Movement Enhancer (HandSOME) devices , , . The HandSOME devices are non-motorized wearable exoskeletons that assists stroke patients with finger and thumb extension movements. The HandSOME I device assists with gross whole hand opening movements, while the HandSOME II assists isolated extension movement of 15 finger and thumb degrees of freedom (DOF), allowing performance of various grip patterns used in ADL. While both devices have been shown to significantly increase range of motion (ROM) and functional ability in chronic stroke subjects ,, the HandSOME devices only assist with extension movements and require enough flexion activity to overcome the assistance of the extension springs. As many stroke patients also suffer finger and thumb flexion weakness, we decided to build upon the work of the high DOF HandSOME II and additionally utilize power actuation so we can assist with both flexion and extension movements.
[Abstract + References] Feasibility of Wearable Sensing for In-Home Finger Rehabilitation Early After Stroke
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