Active Range of Motion Measurement System Using an Optical Sensor to Evaluate Hand Functions.

Impairment of hand function greatly affects the independence of a human being. Proper assessment of hand function before and after any treatment for functional restoration is important to decide better treatment strategies. Despite traditional techniques of hand function evaluation, individual joint based assessment is vital to better track the details of the hand function. Current clinical assessments with goniometers are labour intensive, cumbersome and highly depend on the skill level of the practitioner. This study introduces an active range of motion (AROM) measurement system to measure individual range of motion of finger joints using an optical sensor. The proposed method is highly efficient, and the results demonstrated that the measurements are instant, repeatable and can successfully be employed in a clinical setup for patient evaluations.Clinical Relevance-Closely working with clinician to develop rehabilitation systems, we have identified that the assessment of patient hand functions is time consuming, and accuracy can be depended on the skill level of the practitioner in measuring joint range of motions (ROM). System introduced in this study can measure the joint AROMs instantly and independent of the practitioner's skill level and hence can provide a reliable, repeatable assessment of patient's hand function.

2.5-mm articulated endoluminal forceps using a compliant mechanism.

PURPOSE: Gastrointestinal cancer can be treated using a flexible endoscope through a natural orifice. However, treatment instruments with limited degrees of freedom (DOFs) require a highly skilled operator. Articulated devices useful for endoluminal procedures, such as endoscopic submucosal dissection and biopsy, have been developed. These devices enable dexterous operation in a narrow lumen; however, they suffer from limitations such as large size and high cost. To overcome these limitations, we developed a 2.5-mm articulated forceps that can be inserted into a standard endoscope channel based on a compliant mechanism. METHODS: The compliant mechanism allows the device to be compact and affordable, which is possible due to its monolithic structure. The proposed mechanism consists of two segments, 1-DOF grasping and 2-DOF bending, that are actuated by tendon-sheath mechanisms. A prototype was designed based on finite element analysis results. RESULTS: To confirm the effectiveness of the proposed mechanism, we fabricated the prototype using a 3D printer. A series of mechanical performance tests on the prototype revealed that it achieved the following specifications: (1) DOF: 1-DOF grasping + 2-DOF bending, (2) outer diameter: 2.5 mm, (3) length of the bending segment: 30 mm, and (4) range of motion: [Formula: see text] to [Formula: see text] (grasping) and [Formula: see text] to [Formula: see text] (bending). Finally, we performed a tissue manipulation test on an excised porcine colon and found that a piece of mucous membrane tissue was successfully resected using an electric knife while being lifted with the developed forceps. CONCLUSION: The results of the evaluation experiment demonstrated a positive feasibility of the proposed mechanism, which has a simpler structure compared to those of other conventional mechanisms; furthermore, it is potentially more cost-effective and is disposable. The mechanical design, prototype implementation, and evaluations are reported in this paper.

Towards Control of a Transhumeral Prosthesis with EEG Signals.

Robotic prostheses are expected to allow amputees greater freedom and mobility. However, available options to control transhumeral prostheses are reduced with increasing amputation level. In addition, for electromyography-based control of prostheses, the residual muscles alone cannot generate sufficiently different signals for accurate distal arm function. Thus, controlling a multi-degree of freedom (DoF) transhumeral prosthesis is challenging with currently available techniques. In this paper, an electroencephalogram (EEG)-based hierarchical two-stage approach is proposed to achieve multi-DoF control of a transhumeral prosthesis. In the proposed method, the motion intention for arm reaching or hand lifting is identified using classifiers trained with motion-related EEG features. For this purpose, neural network and k-nearest neighbor classifiers are used. Then, elbow motion and hand endpoint motion is estimated using a different set of neural-network-based classifiers, which are trained with motion information recorded using healthy subjects. The predictions from the classifiers are compared with residual limb motion to generate a final prediction of motion intention. This can then be used to realize multi-DoF control of a prosthesis. The experimental results show the feasibility of the proposed method for multi-DoF control of a transhumeral prosthesis. This proof of concept study was performed with healthy subjects.

Development of a multi-DoF transhumeral robotic arm prosthesis.

An anthropomorphic transhumeral robotic arm prosthesis is proposed in this study. It is capable of generating fifteen degrees-of-freedom, seven active and eight passive. In order to realize wrist motions, a parallel manipulator-based mechanism is proposed. It simulates the human anatomical structure and generates motions in two axes. The hand-of-arm prosthesis consists of under-actuated fingers with intrinsic actuation. The finger mechanism is capable of generating three degrees of freedom, and it exhibits the capability of adjusting the joint angles passively according to the geometry of the grasping object. Additionally, a parameter to evaluate finger mechanisms is introduced, and it measures the adoptability of a finger mechanism. In order to verify the mechanism's efficacy in terms of motion generation, motion simulation and kinematic analysis were carried out. Results demonstrated that the mechanisms are capable of generating the required motions.