Design and development of gripping assistive device for post — Stroke rehabilitation

Report from The National Stroke Association of Malaysia (NASAM), the disease that cause most deaths is stroke which comes after cancer and heart attack. Even though most of the stroke cases is avoidable, rehabilitation will be in high demand. Devices as such has not been created and looking into since the therapist could not fulfil the demand. This project addresses a device to help post - stroke patients to grip and release their fingers as a rehabilitation working process. The system uses leap motion sensor as the input and the output is a servomotor-based exoskeleton. At the moment the system is based on a master-slave mechanism which needs a healthy hand to control the weak hand. The exoskeleton is still being tested on using linear-like actuator mechanisms to perform grasping and extension. © 2017 IEEE

Independent Joint Control of a 3-DOF Robotic System Using PI Controller

The use of robotic devices for repetitive exercising of patients with upper limb sensorimotor impairment has become accepted as effective in rehabilitation therapy. Two forms of rehabilitation robotic devices for upper limb are so far available which include the exoskeleton and end-effector based devices with the emphasis on proper joint coordination and control to actualize effective trajectory tracking and consequently effective therapy. An end-effector based 3 degree of freedom (3-DOF) rehabilitation platform is proposed in this work which uses brushless DC (BLDC) motor for actuation of the two revolute joints. For set-point and trajectory tracking of the revolute joints, each joint and corresponding link has been modeled has a SISO system and a PI compensator has been employed. Preliminary simulation studies showed the effectiveness of the proposed control framework

Non-invasive assessment of affective states on individual with autism spectrum disorder: a review

Individuals with Autism Spectrum Disorder (ASD) are identified as a group of people who have social interaction and communication impairment. They have difficulty in producing speech and explaining what they meant. They also suffer from emotional or cognitive states requirement that stance challenges to their interest in communicating and socializing. Hence, it is vital to know their emotion to help them develop better skills in social interaction. Emotion can be derived from affective states and can be detected through physical reaction and physiological signals. There are numerous known modalities available to detect the affective states either through invasive and non-invasive methods. In order to evaluate the affective states of individuals with ASD, amongst the methods used are through electrodermal activity (EDA), electromyographic (EMG) activity, and cardiovascular activity (ECG) and blood flow analyses. Though considered non invasive, these methods require sensor to be patched on to the skin causing discomfort to the subjects and might distract their true emotion. We propose non-invasive methods which is also contactless to address the problem to detect emotion of individual with ASD that is through thermal imaging. Through the impact of cutaneous temperature in blood flow, thermal imprint is radiated and can be detected in this method. To date, no research has been reported of the use of thermal imaging analysis of facial skin temperature on the individuals with ASD. In this paper we will justify the method and also discuss the merits and demerits of other methods

Development of gripping assistive device for training system

Gripping is an everyday task which goes unnoticeable. Since it is an essential daily movement, without this motion a lot of activities involving this movement could not be done. However due to maturing process and also sometimes mishaps, the grasping movement once in a while become disrupted which then is cause difficulties to whom is influenced. How these impacts, relies upon an individual and also in different ways regardless of age and how the body normally winds up more fragile, less adaptable and less impervious to sickness and damage. Patients with hand gripping issues normally require long term care. This also contributes towards their ability to recover much longer as their regular activity reduces and dependency on other increases. By produce therapy as an, early rehabilitation within the golden period (less than three months prior to incident) is required to improve the gripping motion and regain back the strength of the affected joints as well as muscles. Rehabilitation also helps to improve the patient's ability to return the patient to the level of premorbid function. The current situation is that the rehabilitation process takes longer as there are few physiotherapists available in hospitals. It is anticipated that a mechatronics approach using robotics based devices have been seen as a promising candidate to assist existing forms of the rehabilitation process. The idea is to develop a basic function rehabilitation robot is to support the physiotherapists. The device is aimed to help with the gripping process, where the system is based on a master-slave mechanism which needs a healthy hand to control the weak hand. The system uses a leap motion sensor as the input and the output is an exoskeleton. A gyroscope was used to indicate the finger position and placed on top of the exoskeleton

GLCM correlation approach for blood vessel identification in thermal image

The maturity of detection in emotions via thermal camera is evolving recently since it is able to detect the “hot” parts of human face composition replicating the area of blood vessels. The notion of non-invasive tools for data gatherings via a thermal camera has also been vigorously highlighted. However, to the best of our knowledge, there is no research done to detect emotion of autistic children by using thermal camera. The autistic children are less able to present emotion through facial expression. We hypothesize that, the impact of cutaneous temperature changes due to blood flows in the blood vessels could be correlated to specific emotion state for healthy as well as autistic children. In this work, healthy children were assigned as subjects prior to the development of the algorithm for thermal imaging analysis to form a reference model. Facial thermal distribution was analyzed and a technique using Correlation in Gray Level Co-occurrence Matrices (GLCM) was proposed to identify the region with the presence of blood vessels. A fine k-Nearest Neighbor (k-NN) classifier shows a promising result for the proposed method and suggests that these analyses are momentous for distinguishing between five basic emotions and it could be used as non-verbal mediums to help on autistic children

A hybrid automata framework for an adaptive impedance control of a robot-assisted training system

There is an increasing demand for an effective and adaptive robot-assisted training system for traumatic brain injury patients which can considerably promote their sensorimotor control performance, apart from ensuring the safety of the patients. This study focuses on the impedance control framework to simultaneously track the position trajectory while regulating the apparent impedance of the robot. The framework is based on the hybrid automata model that is used to govern the desired trajectory deployed by the robot-assisted training in assisting rehabilitative motion. A designed experimental setup was developed to evaluate the performance of the proposed hybrid automata scheme. Preliminary simulation results demonstrated the excellent response of the proposed framework with its ability to track the desired trajectory as well as the varying patients' arm impedance profile

Markerless detection of fingertips of object-manipulating hand

Most reported works on fingertip detection focus on extended fingers where the hand is not occluded by another object. This paper proposes a machine-vision-based technique exploiting the contour of the hand and fingers for detecting the fingertips when the hand is manipulating a ball, which means that the fingers are closed and the hand is partially occluded. The preliminary result of our on-going research is promising where it can be used to generate a more objective performance indicator for monitoring the progress during hand therapy by using a digital webcam. Being markerless and contactless, the proposed technique will require minimal preparation prior to the therapy

Assistive-as-needed strategy for upper-limb robotic systems: An initial survey

Stroke is amongst the leading causes of deprivation of one’s ability in carrying out activities of daily living. It has been reported from literature that, the functional recovery of stroke patients are rather poor, unless frequent rehabilitative therapy is assumed on the affected limb. Recent trends of rehabilitation therapy have also shifted towards allowing more participation of the patient in the therapy session rather than simple passive treatments as it has been demonstrated to be non-trivial in promoting neural plasticity to expedite motor recovery process. Therefore, the employment of rehabilitation robotics is seen as a means of mitigating the limitations of conventional rehabilitation therapy. It enables unique methods for promoting patient engagement by providing patients assistance only as needed basis. This paper attempts on reviewing assist-as-needed control strategy applied on upper-limb robotic rehabilitation devices

Multisensor Data Fusion Algorithm for Contactless 3D Position Measurement for Post-Stroke Hand Rehabilitation

Repetitive hand motion exercises help the patients regain their hand motor control. One of the widely used therapies of this type is the patient squeezing a flexible exercise ball in his/her hand repetitively. The exercise balls come at different levels of resistance to accommodate the different levels of limitation of the patients’ hands. However, one of the challenges is to measure objectively the progress that has been made without making any contact such that no additional weights loading the affected arm or hand of the patient. The presence of the exercise ball in the hand adds a degree of difficulty to the problem when an optical solution is adopted. This research attempted to investigate the enabler technology for contactless quantitative measurement system for monitoring the progress in such hand therapy. Evaluation of potential commercial-grade stereo-vision systems have been performed and fingertip detection algorithms have been proposed and evaluated. A total of 4200 images, 2100 fingertip images and 2100 non-fingertip images, were used in the experiment. Our results show that the success rates for the fingertip detection are higher than 94% which demonstrates that the proposed method produces a promising result for fingertip detection for therapy-ball-holding hands

Analysis of point-to-point robotic arm control using PID controller

Point-to-point robotic arm has been used in manufacturing industry to assist company in increasing its production rate. However, the biggest concern in robotic arm is the accuracy for the robot to complete the task of pick-andplace of an object which is dependent on the designed controller. This study investigates the accuracy of the 5 degrees of freedom (DOF) robotic arm model with PID controller. The forward kinematic is analysed systematically in order to determine the required movements for each of the robotic arm joint for its desired operations. The objective of this paper is to simulate the movements of the robotic arm with and without controller by utilizing MATLAB GUI, a microcontroller and servo motors in order to demonstrate the effectiveness of the system. Performance comparison of the robotic arm in completing the pick-and-place task with and without PID is presented in this paper. The preliminary results showed that the difference errors between the desired angular displacement of with and without controller are 0.65%, 3.61%, 10.74%, 82.18% and 44.44% for the five movements