Smart Home Control for Disabled Using Brain Computer Interface

Electroencephalography (EEG) based smart home control system is one of the major applications of Brain Computer Interface (BCI) that allows disabled people to maximize their capabilities at home. A Brain Computer Interface (BCI) is a device that enables severely disabled people to communicate and interact with their environments using their brain waves. In this project, the scope includes Graphical User Interface (GUI) acts as a control and monitoring system for home appliances which using BCI as an input. Hence, NeuroSky MindWave headset is used to detect EEG signal from brain. Furthermore, a prototype model is developed using Raspberry Pi 3 Model B+, 4 channels 5V relay module, light bulb and fan. The raw data signal from brain wave is being extracted to operate the home appliances. Besides, the results agree well with the command signal used during the experiment. Lastly, the developed system can be easily implemented in smart homes and has high potential to be used in smart automation

Force Control for One Degree of Freedom Haptic Device using PID Controller

Haptics has been used as an additional feedback to increase human experience to the environment over years and its application has been widening into education, manufacturing and medical. The most developed haptic devices are for rehabilitation purpose. The rehabilitation process usually depends on the physiotherapist. But, it requires repetitive movements for long-term rehabilitation, thus haptic devices are needed. Most of the rehabilitation devices are included with haptic feedback to enhance therapy exercise during the rehabilitation process. However, the devices come with multiple degrees of freedom (DOF), complex design and costly. Rehabilitation for hand movement such as grasping, squeezing, holding and pinching usually does not need an expensive and complex device. Therefore, the goal of this study is to make an enhancement to One DOF Haptic Device for grasping rehabilitation exercise. It is improved to perform a force control mechanism with few types of conventional controller which are Proportional (P) controller, Proportional-Integral (PI) controller, Proportional-Derivative (PD) controller and Proportional-Integral-Derivative (PID) controller. The performance of the haptic device is tested with different conventional controller to obtain the best proposed controller based on the lowest value of Mean Square Error (MSE). The results show that PID Controller (MSE = 0.0028) is the most suitable for the haptic device with Proportional gain (Kp), Integral gain (Ki) and Derivative gain (Kd) are 1.3, 0.01 and 0.2 respectively. The force control mechanism can imitate the training motion of grasping movement for the patient

Non-motorised Rehabilitation Device for Performance Assessment in Upper Limb Stroke Rehabilitation: A Pilot Study

Stroke patients with upper limb disability restricted to carry out their activities of daily living. The patient needs a motivation to recover from a stroke and the patient also needs to go through a rehabilitation process at the same time. The conventional rehabilitation process scoring systems are always subjective, lack reliability and relies heavily on the ability of the trained physiotherapist that providing only rough estimates on motor function. On the other hand, robot-based assessments are objective, repeatable, and could potentially reduce the assessment time. Therefore, a simple non-motorized device was developed as a tool to objectively assess hand function of stroke patients. This study was carried out to investigate the suitability of using the developed device with stroke patient populations and to evaluate the performance of clinical scores prediction of the stroke patients. A total of five patients with upper limb disability following stroke consented to take part in this study. Twelve predictive variables were investigated, relating to the total movement time, velocity, strategy, accuracy, and smoothness from three robotic assessment modules which are Draw I, Draw Diamond and Draw Circle. As the result, there is a potential of using this rehabilitation device in stroke population for assessing the upper limb performance. In addition to that, a new developed hardware for measuring elbow angle was proposed to be used for identifying the shoulder movement that can be used in conjunction with kinematic variables to carry out the data acquisition process in the future for improvement of effectiveness and accuracy of the robotic assessment

Non-motorised Rehabilitation Device for Performance Assessment in Upper Limb Stroke Rehabilitation: A Pilot Study

Stroke patients with upper limb disability restricted to carry out their activities of daily living. The patient needs a motivation to recover from a stroke and the patient also needs to go through a rehabilitation process at the same time. The conventional rehabilitation process scoring systems are always subjective, lack reliability and relies heavily on the ability of the trained physiotherapist that providing only rough estimates on motor function. On the other hand, robot-based assessments are objective, repeatable, and could potentially reduce the assessment time. Therefore, a simple non-motorized device was developed as a tool to objectively assess hand function of stroke patients. This study was carried out to investigate the suitability of using the developed device with stroke patient populations and to evaluate the performance of clinical scores prediction of the stroke patients. A total of five patients with upper limb disability following stroke consented to take part in this study. Twelve predictive variables were investigated, relating to the total movement time, velocity, strategy, accuracy, and smoothness from three robotic assessment modules which are Draw I, Draw Diamond and Draw Circle. As the result, there is a potential of using this rehabilitation device in stroke population for assessing the upper limb performance. In addition to that, a new developed hardware for measuring elbow angle was proposed to be used for identifying the shoulder movement that can be used in conjunction with kinematic variables to carry out the data acquisition process in the future for improvement of effectiveness and accuracy of the robotic assessment