Advancing the Functionality and Wearability of Robotic Hand Orthoses Towards Activities of Daily Living in Stroke Patients

Post stroke rehabilitation is effective when a large number of motor repetitions are provided to patients. However, conventional physical therapy or traditional desktop-size robot aided rehabilitation do not provide sufficient number of repetitions due to cost and logistical barriers. Our vision is to realize a wearable and functional hand orthosis that could be used outside of controlled, clinical settings, thus allowing for more training repetitions. Furthermore, if such a device can prove effective for Activities of Daily Living (ADLs) while actively worn, this can incentivize patients to increase its use, further enhancing rehabilitative effects. However, in order to provide such clinical benefits, the device must be completely wearable without obtrusive features, and intuitive to control even for non-experts. In this thesis, we thus focus on wearability, functionality, and intuitive intent detection technology for a novel hand robot, and assess its performance when used both as a rehabilitative device and an assistive tool. A fully wearable device must deliver meaningful manipulation capability in small and lightweight package. In this context, we investigate the capability of single-actuator devices to assist whole hand movement patterns through a network of exotendons. Our prototypes combine a single linear actuator (mounted on a forearm splint) with a network of exotendons (routed on the surface of a soft glove). We investigate two possible tendon network configurations: one that produces full finger extension (overcoming flexor spasticity) and one that combines proximal flexion with distal extension at each finger. In experiments with stroke survivors, we measure the force levels needed to overcome various levels of spasticity and to open the hand for grasping using the first of these configurations, and qualitatively demonstrate the ability to execute fingertip grasps using the second. Our results support the feasibility of developing future wearable devices able to assist a range of manipulation tasks. In order to further improve the wearability of the device, we propose two designs that provide effective force transmission by increasing moment arms around finger joints. We evaluate the designs with geometric models and experiment using a 3D-printed artificial finger to find force and joint angle characteristics of the suggested structures. We also perform clinical tests with stroke patients to demonstrate the feasibility of the designs. The testing supports the hypothesis that the proposed designs efficiently elicit extension of the digits in patients with spasticity as compared to existing baselines. With the suggested transmission designs, the device can deliver sufficient extension force even when the users have increased muscle tone due to fatigue. The vision of an orthotic device used for ADLs can only be realized if the patients are able to operate the device themselves. However, the field is generally lacking effective methods by which the user can operate the device: such controls must be effective, intuitive, and robust to the wide range of possible impairment patterns. The variety of encountered upper limb impairment patterns in stroke patients means that a single sensing modality, such as electromyography, might not be sufficient to enable controls for a broad range of users. To address this significant gap, we introduce a multimodal sensing and interaction paradigm for an active hand orthosis. In our proof-of-concept implementation, EMG is complemented by other sensing modalities, such as finger bend and contact pressure sensors. We propose multimodal interaction methods that utilize this sensory data as input, and show they can enable tasks for stroke survivors who exhibit different impairment patterns. We then assess the performance of the robotic orthosis for two possible roles: as a therapeutic tool that facilitates device mediated hand exercises to recover neuromuscular function, or as an assistive device for use in everyday activities to aid functional use of the hand. 11 chronic stroke (> 2 years) patients with moderate muscle tone (Modified Ashworth Scale ≤ 2 in upper extremity) engage in a month-long training protocol using the orthosis. Individuals are evaluated using standardized outcome measures, both with and without orthosis assistance. The results highlight the potential for wearable and user-driven robotic hand orthoses to extend the use and training of the affected upper limb after stroke. The advances proposed in this thesis have the potential to enable robotic based hand rehabilitation during daily activities (as opposed to isolated hand exercises with limited upper limb engagement) and over extended periods of time, even in a patient’s home environment. Numerous challenges must still be overcome in order to achieve this vision, related to design (compact devices with easier donning/doffing), control (robust yet intuitive intent inferral), and effectiveness (improved functionality in a wider range of metrics). However, if these challenges can be addressed, wearable robotic devices have the potential to greatly extend the use and training of the affected upper limb after stroke, and help improve the quality of life for a large patient population

DESIGN AND ANALYSIS OF A 3D-PRINTED, THERMOPLASTIC ELASTOMER (TPE) SPRING ELEMENT FOR USE IN CORRECTIVE HAND ORTHOTICS

This thesis proposes an algorithm that determine the geometry of 3D-printed, custom-designed spring element bands made of thermoplastic elastomer (TPE) for use in a wearable orthotic device to aid in the physical therapy of a human hand exhibiting spasticity after stroke. Each finger of the hand is modeled as a mechanical system consisting of a triple-rod pendulum with nonlinear stiffness at each joint and forces applied at the attachment point of each flexor muscle. The system is assumed quasi-static, which leads to a torque balance between the flexor tendons in the hand, joint stiffness and the design force applied to the fingertip by the 3D-printed spring element. To better understand material properties of the spring element’s material, several tests are performed on TPE specimens printed with different infill geometries, including tensile tests and cyclic loading tests. The data and stress-strain curves for each geometry type are presented, which yield a nonlinear relationship between stress and strain as well as apparent hysteresis. Polynomial curves are used to fit the data, which allows for the band geometry to be designed. A hypothetical hand is presented along with how input measurements might be taken for the algorithm. The inputs are entered into the algorithm, and the geometry of the bands for each finger are generated. Results are discussed, and future work is noted, providing a means for the design of a customized orthotic device

MOSAR: A Soft-Assistive Mobilizer for Upper Limb Active Use and Rehabilitation

In this study, a soft assisted mobilizer called MOSAR from (Mobilizador Suave de Asistencia y Rehabilitación) for upper limb rehabilitation was developed for a 11 years old child with right paretic side. The mobilizer provides a new therapeutic approach to augment his upper limb active use and rehabilitation, by means of exerting elbow (flexion-extension), forearm (pronation-supination) and (flexion-extension along with ulnar-radial deviations) at the wrist. Preliminarily, the design concept of the soft mobilizer was developed through Reverse Engineering of his upper limb: first casting model, silicone model, and later computational model were obtained by 3D scan, which was the parameterized reference for MOSAR development. Then, the manufacture of fabric inflatable soft actuators for driving the MOSAR system were carried out. Lastly, a law close loop control for the inflation-deflation process was implemented to validate FISAs performance. The results demonstrated the feasibility and effectiveness of the FISAs for being a functional tool for upper limb rehabilitation protocols by achieving those previous target motions similar to the range of motion (ROM) of a healthy person or being used in other applications

What is Task-Oriented Training? A Scoping Review

Task-Oriented Training (TOT) is an proven stroke rehabilitation intervention with significant evidence-based research that supports its effectiveness. The absence of a clear definition has led to variability in research reporting and subsequent confusion with practical implementation. A consistent definition seeks to remedy this ambiguity to facilitate knowledge translation. The objective of this study was to determine a comprehensive definition of TOT that encapsulates previous definitions and descriptions in the literature. In order to derive this definition, a two stage scoping review process was conducted across four databases searching for articles on the use of TOT in adult stroke rehabilitation therapy. The analysis of this scoping review included 174 articles. Commonly found words used to define TOT included: repetitive, functional, task practice, task specific, task oriented, intensity, and client-centered. Other salient words that aligned with the principles of neuroplasticity and key components of TOT were meaningful, progressive, graded, variable, and feedback. Based on these findings, a comprehensive proposed definition is as follows: Task-oriented training is an effective stroke rehabilitation intervention that focuses on the use of client-centered, repetitive practice of activities that are of high intensity and meaningful to the client. In conclusion, although similar principles were described in the TOT literature, there was no consistent and comprehensive definition of TOT. This scoping review identified key concepts from TOT methodology, and discussion sections in rehabilitation literature to generate a proposed comprehensive definition of TOT to guide research and practice

Improving Kinematic Accuracy of Soft Wearable Data Gloves by Optimizing Sensor Locations

Bending sensors enable compact, wearable designs when used for measuring hand configurations in data gloves. While existing data gloves can accurately measure angular displacement of the finger and distal thumb joints, accurate measurement of thumb carpometacarpal (CMC) joint movements remains challenging due to crosstalk between the multi-sensor outputs required to measure the degrees of freedom (DOF). To properly measure CMC-joint configurations, sensor locations that minimize sensor crosstalk must be identified. This paper presents a novel approach to identifying optimal sensor locations. Three-dimensional hand surface data from ten subjects was collected in multiple thumb postures with varied CMC-joint flexion and abduction angles. For each posture, scanned CMC-joint contours were used to estimate CMC-joint flexion and abduction angles by varying the positions and orientations of two bending sensors. Optimal sensor locations were estimated by the least squares method, which minimized the difference between the true CMC-joint angles and the joint angle estimates. Finally, the resultant optimal sensor locations were experimentally validated. Placing sensors at the optimal locations, CMC-joint angle measurement accuracies improved (flexion, 2.8° ± 1.9°; abduction, 1.9° ± 1.2°). The proposed method for improving the accuracy of the sensing system can be extended to other types of soft wearable measurement devices

Low-cost Rigid-frame Exoskeleton Glove with Finger-joint Flexion Tracking Mapped onto a Robotic Hand

This thesis provides a representation of a low-cost rigid-frame exoskeleton glove that is used to track finger-joint flexion mapped onto a robotic hand to mimic user movements. The overall setup consists of an exoskeleton glove (exo-glove), sensors, a microcontroller, and a telerobotic hand. The design of the exo-glove is crafted to fit onto a left hand. SolidWorks was used for the prototype designs which were then sent to the Stratasys 400 rapid prototyping machine to be 3D printed in ABS-M30 plastic. The exo-glove houses five rotary position sensors and three flexible sensors to track angle changes of the finger joints from two fingers and a thumb. Five low-pass filters are implemented as signal filtering for the rotary position sensors. An Arduino Mega microcontroller is connected to the sensors of the exo-glove and processes the input values. Using an open-loop controller to control the robotic hand, the values processed by the microcontroller from the exo-glove are sent to the servo motors on the robotic hand to operate the corresponding fingers of the user. Throughout the initial calibration and testing phase, each sensor was tested individually to ensure the sensor functionally performs well. Signal analysis was conducted on the sensors at steady state and while in operation to show fluctuations in sensor readings and response to finger flexion. Experimental results show that averaging sensor data in the processing code yields smoother values and better precision. Due to the use of low-pass filtering with the rotary position sensors, the data sets collected were grouped together tightly compared to the flex sensors without filtering. However, the actual angles measured were not accurately portrayed in sensor readings. The true flexion angles were compared in the data samplings to find a variety of ranges spanning around the angles desired to track. Many of the actual flexion angles were offset from the sensor readings by a variation of degrees, but the data shows the sensor readings were able to follow the general magnitude of the true flexion angles. The precision seen in the data was also apparent in the robotic hand mirroring the posture. Changes in sensor readings caused jerking movements to occur in the robotic fingers but were able to maintain an overall flexion mirroring of the RF exo-glove. There is quarter-second delay between the exo-glove sensor reading and the robotic hand mirroring capability when not implementing averaging. When averaging the sensor values, there was a delay of more than half a second between the exo-glove posture and robotic hand mirroring

Concept of an exoskeleton for industrial applications with modulated impedance based on Electromyographic signal recorded from the operator

The introduction of an active exoskeleton that enhances the operator power in the manufacturing field was demonstrated in literature to lead to beneficial effects in terms of reducing fatiguing and the occurrence of musculo-skeletal diseases. However, a large number of manufacturing operations would not benefit from power increases because it rather requires the modulation of the operator stiffness. However, in literature, considerably less attention was given to those robotic devices that regulate their stiffness based on the operator stiffness, even if their introduction in the line would aid the operator during different manipulations respect with the exoskeletons with variable power. In this thesis the description of the command logic of an exoskeleton for manufacturing applications, whose stiffness is modulated based on the operator stiffness, is described. Since the operator stiffness cannot be mechanically measured without deflecting the limb, an estimation based on the superficial Electromyographic signal is required. A model composed of 1 joint and 2 antagonist muscles was developed to approximate the elbow and the wrist joints. Each muscle was approximated as the Hill model and the analysis of the joint stiffness, at different joint angle and muscle activations, was performed. The same Hill muscle model was then implemented in a 2 joint and 6 muscles (2J6M) model which approximated the elbow-shoulder system. Since the estimation of the exerted stiffness with a 2J6M model would be quite onerous in terms of processing time, the estimation of the operator end-point stiffness in realtime would therefore be questionable. Then, a linear relation between the end-point stiffness and the component of muscle activation that does not generate any end-point force, is proposed. Once the stiffness the operator exerts was estimated, three command logics that identifies the stiffness the exoskeleton is required to exert are proposed. These proposed command logics are: Proportional, Integral 1 s, and Integral 2 s. The stiffening exerted by a device in which a Proportional logic is implemented is proportional, sample by sample, to the estimated stiffness exerted by the operator. The stiffening exerted by the exoskeleton in which an Integral logic is implemented is proportional to the stiffness exerted by the operator, averaged along the previous 1 second (Integral 1 s) or 2 seconds (Integral 2 s). The most effective command logic, among the proposed ones, was identified with empirical tests conducted on subjects using a wrist haptic device (the Hi5, developed by the Bioengineering group of the Imperial College of London). The experimental protocol consisted in a wrist flexion/extension tracking task with an external perturbation, alternated with isometric force exertion for the estimation of the occurrence of the fatigue. The fatigue perceived by the subject, the tracking error, defined as the RMS of the difference between wrist and target angles, and the energy consumption, defined as the sum of the squared signals recorded from two antagonist muscles, indicated the Integral 1 s logic to be the most effective for controlling the exoskeleton. A logistic relation between the stiffness exerted by the subject and the stiffness exerted by the robotic devices was selected, because it assured a smooth transition between the maximum and the minimum stiffness the device is required to exert. However, the logistic relation parameters are subject-specific, therefore an experimental estimation is required. An example was provided. Finally, the literature about variable stiffness actuators was analyzed to identify the most suitable device for exoskeleton stiffness modulation. This actuator is intended to be integrated on an existing exoskeleton that already enhances the operator power based on the operator Electromyographic signal. The identified variable stiffness actuator is the DLR FSJ, which controls its stiffness modulating the preload of a single spring