The assist-as-needed technique in robotic rehabilitation is a popular technique that encourages patients’ active participation to promote motor recovery. It has been proven beneficial for patients with functional motor disability. However, its application in robotic therapy has been hindered by a poor estimation method of subjects’ functional or movement ability which is required for setting the appropriate robotic assistance. Moreover, there is also the need for consistency and repeatability of the functional ability estimation in line with the clinical procedure to facilitate a wider clinical adoption. In this study, we propose a new technique of estimation of subject’s functional ability based on the Wolf Motor Function Test. We called this estimation the functional ability index. The functional ability index enables the modulation of robotic assistance and gives a more consistent indication of subjects’ upper-limb movement ability during therapy session. Our baseline controller is an adaptive inertia-related controller, which is integrated with the functional ability index algorithm to provide movement assistance as when needed. Experimental studies are conducted on three hemiplegic patients with different levels of upper-limb impairments. Each patient is requested to perform reaching task of lifting a can from table-to-mouth according to the guidelines stipulated in the Wolf Motor Function Test. Data were collected using two inertial measurement unit sensors installed at the flexion/extension joints, and the functional ability score of each patient was rated by an experienced therapist. Results showed that the proposed functional ability index algorithm can estimate patients’ functional ability level consistently with clinical procedure and can modify generated robotic assistance in accordance with patients’ functional movement ability.

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Upper limb disability is one of the major adversities faced by post-stroke patients. Eating is one of the fundamental activities of survival for all living beings. The robotic rehabilitation systems for people with upper limb disabilities must have the capability of assisting the patients, providing appropriate forces/torques, during various eating activities. In this study, a 3-D, four-DOF dynamic , mathematical model of human arm , including wrist and elbow joints, focusing on elbow flexion/extension motion, forearm pronation/supination, wrist flexion/extension and wrist adduction/abduction is formulated, for predicting the torques during different eating activities. A simulation study and experimental validation has been conducted involving five different food types and using two types of cutlery, which are, a fork and a spoon, to study their effect on the corresponding torques produced. It was observed that the maximum torque is obtained in both wrist and elbow joint when the subject digs into the food and eats (event B) in the majority of the eating tasks. The accuracy of the model, in terms of torque prediction, was compared to that of the load cell, for all eating activities, using RMSE as a statistical measure, to the test the performance of the model. The results indicate that 3-D dynamic model formulated fits all the torques for all eating activities very well, with the average RMSE of 0.05 Nm and the performance of the model is good. These results verify that the proposed Kane 's model, successfully models the HUL, during different eating tasks and using different types of cutlery.

Abstract-Fuzzy logic enables designers to control complex systems more effectively than traditional approaches as it provides a simple way to arrive at a definite conclusion upon ambiguous, imprecise or noisy information. In this paper, we describe the development of two miniature LEGO robots, which are the line following and the light searching mobile robots to provide a better understanding of fuzzy logic control theory and real life application for an undergraduate training system. This study is divided into two parts. In the first part, an object sorter robot is built to perform pick and place task to load different colour objects on a fuzzy logic controlled line following robot which then carries the preloaded objects to a goal by following a white line. In the second part, an intelligent fuzzy logic controlled light searching robot with the capability to navigate in a maze is developed. All of the robots are constructed by using the LEGO Mindstorms kit. Interactive C programming language is used to program fuzzy logic robots. Experimental results show that the robots has successfully track the predefined path and navigate towards light source under the influence of the fuzzy logic controller; and therefore can be used as a training system in undergraduate fuzzy logic class.

Continuous Passive Machines (CPM) facilitate patients in eliminating joint stiffness after surgery and lead to a faster and more efficient recovery. However, many previous CPM machined are mechanically complicated, expensive, and lack a user interface. This paper presents a new CPM machine for elbow flexion-extension and forearm pronation-supination. The machine is simple, low-cost, and equipped with Graphical User Interface (GUI). Its mechanism is designed so that it can be used on the left or right arms interchangeably. It is developed using aluminum, perspex, and steel rods. The electrical part of the machine consists of Arduino Uno to drive the motors and a potentiometer to measure the patients’ Range of Motion (ROM). The GUI for setting the exercise parameters and monitoring the patients’ progress has been developed using MATLAB software. The experimental results show that the machine has successfully provided the repetitive desired motions. The machine realizes elbow flexion-extension and forearm pronation-supination movements with 0ᵒ-135ᵒ and 0ᵒ-90ᵒ ranges of motion (ROM), respectively. The machine is also capable of increasing the elbow joint’s ROM by 5ᵒ increments for the therapy. The results show that the machine has the potential to be used in hospitals and rehabilitation centers.

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