Integrated optical fiber force myography sensor as pervasive predictor of hand postures

Force myography (FMG) is an appealing alternative to traditional electromyography in biomedical applications, mainly due to its simpler signal pattern and immunity to electrical interference. Most FMG sensors, however, send data to a computer for further processing, which reduces the user mobility and, thus, the chances for practical application. In this sense, this work proposes to remodel a typical optical fiber FMG sensor with smaller portable components. Moreover, all data acquisition and processing routines were migrated to a Raspberry Pi 3 Model B microprocessor, ensuring the comfort of use and portability. The sensor was successfully demonstrated for 2 input channels and 9 postures classification with an average precision and accuracy of ~99.5% and ~99.8%, respectively, using a feedforward artificial neural network of 2 hidden layers and a competitive output layer11CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPNão tem0012017/25666-

Design and Prototyping of a Bio-inspired Kinematic Sensing Suit for the Shoulder Joint: Precursor to a Multi-DoF Shoulder Exosuit

Soft wearable robots are a promising new design paradigm for rehabilitation and active assistance applications. Their compliant nature makes them ideal for complex joints like the shoulder, but intuitive control of these robots require robust and compliant sensing mechanisms. In this work, we introduce the sensing framework for a multi-DoF shoulder exosuit capable of sensing the kinematics of the shoulder joint. The proposed tendon-based sensing system is inspired by the concept of muscle synergies, the body's sense of proprioception, and finds its basis in the organization of the muscles responsible for shoulder movements. A motion-capture-based evaluation of the developed sensing system showed conformance to the behaviour exhibited by the muscles that inspired its routing and validates the hypothesis of the tendon-routing to be extended to the actuation framework of the exosuit in the future. The mapping from multi-sensor space to joint space is a multivariate multiple regression problem and was derived using an Artificial Neural Network (ANN). The sensing framework was tested with a motion-tracking system and achieved performance with root mean square error (RMSE) of approximately 5.43 degrees and 3.65 degrees for the azimuth and elevation joint angles, respectively, measured over 29000 frames (4+ minutes) of motion-capture data.Comment: 8 pages, 7 figures, 1 tabl

Nonlinearity Compensation in a Multi-DoF Shoulder Sensing Exosuit for Real-Time Teleoperation

The compliant nature of soft wearable robots makes them ideal for complex multiple degrees of freedom (DoF) joints, but also introduce additional structural nonlinearities. Intuitive control of these wearable robots requires robust sensing to overcome the inherent nonlinearities. This paper presents a joint kinematics estimator for a bio-inspired multi-DoF shoulder exosuit capable of compensating the encountered nonlinearities. To overcome the nonlinearities and hysteresis inherent to the soft and compliant nature of the suit, we developed a deep learning-based method to map the sensor data to the joint space. The experimental results show that the new learning-based framework outperforms recent state-of-the-art methods by a large margin while achieving 12ms inference time using only a GPU-based edge-computing device. The effectiveness of our combined exosuit and learning framework is demonstrated through real-time teleoperation with a simulated NAO humanoid robot.Comment: 8 pages, 7 figures, 3 tables. Accepted to be published in IEEE RoboSoft 202

Wearable Sensor Systems for Human Motion Measurement

Department of Mechanical EngineeringIn this thesis, various wearable sensor systems were developed to measure human motions. Measured human motion included the gait motion of lower extremity and finger motion. The gait motion was measured by using inertial measurement units (IMUs) and manually developed ground reaction force (GRF) sensors. Four IMUs measured hip, knee and ankle joint angles by calculating rotational matrix of each sensor. Four GRF sensors were made of silicone tube and pressure sensors that measured pressure changes inside the tubes. The measured joint angles and GRF by developed system were compared with a camera-based motion capture system and a fixed force plate. On the other hand, a wearable soft sensor system was developed to measure finger motions, which consisted of soft and stretchable silicone filled with the electro-conductive liquid metal, called eutectic Gallium-Indium(EGaIn) alloy. Due to the light weight and highly stretchable properties of the silicone, the wearable sensor system allowed natural movements for the users and it was able to adapt to various hand sizes. In the proposed system, the flexion and extension of fingers and abduction of index finger could be measured. The accuracy in finger motion measurement was verified by the camera-based motion capture system. Lastly, a modeling of human joint with 3 degrees of freedom (DOFs) was investigated. The purpose of the modeling was to model the carpometacarpal (CMC) joint of the thumb more precisely. The glenohumeral (GH) joint was used to verify the model due to its similar behavior with CMC joint. The result was validated by using a camera-based motion capture system.ope

Updated Perspectives on the Role of Biomechanics in COPD: Considerations for the Clinician

Patients with chronic obstructive pulmonary disease (COPD) demonstrate extra-pulmonary functional decline such as an increased prevalence of falls. Biomechanics offers insight into functional decline by examining mechanics of abnormal movement patterns. This review discusses biomechanics of functional outcomes, muscle mechanics, and breathing mechanics in patients with COPD as well as future directions and clinical perspectives. Patients with COPD demonstrate changes in their postural sway during quiet standing compared to controls, and these deficits are exacerbated when sensory information (eg, eyes closed) is manipulated. If standing balance is disrupted with a perturbation, patients with COPD are slower to return to baseline and their muscle activity is differential from controls. When walking, patients with COPD appear to adopt a gait pattern that may increase stability (eg, shorter and wider steps, decreased gait speed) in addition to altered gait variability. Biomechanical muscle mechanics (ie, tension, extensibility, elasticity, and irritability) alterations with COPD are not well documented, with relatively few articles investigating these properties. On the other hand, dyssynchronous motion of the abdomen and rib cage while breathing is well documented in patients with COPD. Newer biomechanical technologies have allowed for estimation of regional, compartmental, lung volumes during activity such as exercise, as well as respiratory muscle activation during breathing. Future directions of biomechanical analyses in COPD are trending toward wearable sensors, big data, and cloud computing. Each of these offers unique opportunities as well as challenges. Advanced analytics of sensor data can offer insight into the health of a system by quantifying complexity or fluctuations in patterns of movement, as healthy systems demonstrate flexibility and are thus adaptable to changing conditions. Biomechanics may offer clinical utility in prediction of 30-day readmissions, identifying disease severity, and patient monitoring. Biomechanics is complementary to other assessments, capturing what patients do, as well as their capability

Design and Evaluation of a Customized and Body-powered Prosthesis using Fingertip Trajectories based on Polar Coordinate Analysis

Department of Mehcanical EngineeringThis thesis presents a design and evaluation of a customized finger prosthesis that generates a natural finger motion. The design of the prosthesis followed two primary requirements: i) the size of the prosthesis should reflect that of an amputee???s finger; ii) the prosthesis should enable the natural finger motion of the amputee. To achieve these aims, two methods were employed: i) an incomplete four-bar mechanism by utilizing the remaining joint of a subject as the joint in the mechanism; ii) a fingertip trajectory analysis in polar coordinates to model the natural finger motion as only one degree of freedom (DOF). A serially connected incomplete four-bar mechanism was applied to create an under-actuation system. The under-actuation system operated by a metacarpophalangeal (MCP) joint rotation of the amputee which makes proximal interphalangeal (PIP) and distal interphalangeal (DIP) joint rotations. The system does not need any actuators to control the two joint rotations, but employs the residuum of the amputee as an actuator. The fingertip trajectory was considered as the typical factor to represent the natural finger motion, and a new curve fitting method in the polar coordinate of the fingertip trajectory was proposed. The method represents not only the finger motion of a single subject but also of people in general using the same order equation. To make the proposed mechanism move like the natural finger motion of the amputee, a fingertip trajectory curve from the curve fitting method was used as a reference for the mechanism in an optimization process. During the optimization process, the design variables were chosen by considering data from the finger amputee (e.g. residuum size, expected phalangeal lengths, etc.) as well as the requirements of the finger prosthesis. A modular wearable interface was proposed to allow the system to be worn easily and the system joint to be manually aligned to the finger joint accurately. As we focused on the design of the finger prosthesis, the prototype was manufactured based on the finger information of a normal subject before applying it to the actual finger amputee. The performance of the proposed system was verified by intensive experiments for grasping and manipulation while wearing the proposed system.clos