Distributed Sensing and Stimulation Systems Towards Sense of Touch Restoration in Prosthetics

Modern prostheses aim at restoring the functional and aesthetic characteristics of the lost limb. To foster prosthesis embodiment and functionality, it is necessary to restitute both volitional control and sensory feedback. Contemporary feedback interfaces presented in research use few sensors and stimulation units to feedback at most two discrete feedback variables (e.g. grasping force and aperture), whereas the human sense of touch relies on a distributed network of mechanoreceptors providing high-fidelity spatial information. To provide this type of feedback in prosthetics, it is necessary to sense tactile information from artificial skin placed on the prosthesis and transmit tactile feedback above the amputation in order to map the interaction between the prosthesis and the environment. This thesis proposes the integration of distributed sensing systems (e-skin) to acquire tactile sensation, and non-invasive multichannel electrotactile feedback and virtual reality to deliver high-bandwidth information to the user. Its core focus addresses the development and testing of close-loop sensory feedback human-machine interface, based on the latest distributed sensing and stimulation techniques for restoring the sense of touch in prosthetics. To this end, the thesis is comprised of two introductory chapters that describe the state of art in the field, the objectives and the used methodology and contributions; as well as three studies distributed over stimulation system level and sensing system level. The first study presents the development of close-loop compensatory tracking system to evaluate the usability and effectiveness of electrotactile sensory feedback in enabling real-time close-loop control in prosthetics. It examines and compares the subject\u2019s adaptive performance and tolerance to random latencies while performing the dynamic control task (i.e. position control) and simultaneously receiving either visual feedback or electrotactile feedback for communicating the momentary tracking error. Moreover, it reported the minimum time delay needed for an abrupt impairment of users\u2019 performance. The experimental results have shown that electrotactile feedback performance is less prone to changes with longer delays. However, visual feedback drops faster than electrotactile with increased time delays. This is a good indication for the effectiveness of electrotactile feedback in enabling close- loop control in prosthetics, since some delays are inevitable. The second study describes the development of a novel non-invasive compact multichannel interface for electrotactile feedback, containing 24 pads electrode matrix, with fully programmable stimulation unit, that investigates the ability of able-bodied human subjects to localize the electrotactile stimulus delivered through the electrode matrix. Furthermore, it designed a novel dual parameter -modulation (interleaved frequency and intensity) and compared it to conventional stimulation (same frequency for all pads). In addition and for the first time, it compared the electrotactile stimulation to mechanical stimulation. More, it exposes the integration of virtual prosthesis with the developed system in order to achieve better user experience and object manipulation through mapping the acquired real-time collected tactile data and feedback it simultaneously to the user. The experimental results demonstrated that the proposed interleaved coding substantially improved the spatial localization compared to same-frequency stimulation. Furthermore, it showed that same-frequency stimulation was equivalent to mechanical stimulation, whereas the performance with dual-parameter modulation was significantly better. The third study presents the realization of a novel, flexible, screen- printed e-skin based on P(VDF-TrFE) piezoelectric polymers, that would cover the fingertips and the palm of the prosthetic hand (particularly the Michelangelo hand by Ottobock) and an assistive sensorized glove for stroke patients. Moreover, it developed a new validation methodology to examine the sensors behavior while being solicited. The characterization results showed compatibility between the expected (modeled) behavior of the electrical response of each sensor to measured mechanical (normal) force at the skin surface, which in turn proved the combination of both fabrication and assembly processes was successful. This paves the way to define a practical, simplified and reproducible characterization protocol for e-skin patches In conclusion, by adopting innovative methodologies in sensing and stimulation systems, this thesis advances the overall development of close-loop sensory feedback human-machine interface used for restoration of sense of touch in prosthetics. Moreover, this research could lead to high-bandwidth high-fidelity transmission of tactile information for modern dexterous prostheses that could ameliorate the end user experience and facilitate it acceptance in the daily life

Human-Machine Interfaces using Distributed Sensing and Stimulation Systems

As the technology moves towards more natural human-machine interfaces (e.g. bionic limbs, teleoperation, virtual reality), it is necessary to develop a sensory feedback system in order to foster embodiment and achieve better immersion in the control system. Contemporary feedback interfaces presented in research use few sensors and stimulation units to feedback at most two discrete feedback variables (e.g. grasping force and aperture), whereas the human sense of touch relies on a distributed network of mechanoreceptors providing a wide bandwidth of information. To provide this type of feedback, it is necessary to develop a distributed sensing system that could extract a wide range of information during the interaction between the robot and the environment. In addition, a distributed feedback interface is needed to deliver such information to the user. This thesis proposes the development of a distributed sensing system (e-skin) to acquire tactile sensation, a first integration of distributed sensing system on a robotic hand, the development of a sensory feedback system that compromises the distributed sensing system and a distributed stimulation system, and finally the implementation of deep learning methods for the classification of tactile data. It\u2019s core focus addresses the development and testing of a sensory feedback system, based on the latest distributed sensing and stimulation techniques. To this end, the thesis is comprised of two introductory chapters that describe the state of art in the field, the objectives, and the used methodology and contributions; as well as six studies that tackled the development of human-machine interfaces

Novel Bidirectional Body - Machine Interface to Control Upper Limb Prosthesis

Objective. The journey of a bionic prosthetic user is characterized by the opportunities and limitations involved in adopting a device (the prosthesis) that should enable activities of daily living (ADL). Within this context, experiencing a bionic hand as a functional (and, possibly, embodied) limb constitutes the premise for mitigating the risk of its abandonment through the continuous use of the device. To achieve such a result, different aspects must be considered for making the artificial limb an effective support for carrying out ADLs. Among them, intuitive and robust control is fundamental to improving amputees’ quality of life using upper limb prostheses. Still, as artificial proprioception is essential to perceive the prosthesis movement without constant visual attention, a good control framework may not be enough to restore practical functionality to the limb. To overcome this, bidirectional communication between the user and the prosthesis has been recently introduced and is a requirement of utmost importance in developing prosthetic hands. Indeed, closing the control loop between the user and a prosthesis by providing artificial sensory feedback is a fundamental step towards the complete restoration of the lost sensory-motor functions. Within my PhD work, I proposed the development of a more controllable and sensitive human-like hand prosthesis, i.e., the Hannes prosthetic hand, to improve its usability and effectiveness. Approach. To achieve the objectives of this thesis work, I developed a modular and scalable software and firmware architecture to control the Hannes prosthetic multi-Degree of Freedom (DoF) system and to fit all users’ needs (hand aperture, wrist rotation, and wrist flexion in different combinations). On top of this, I developed several Pattern Recognition (PR) algorithms to translate electromyographic (EMG) activity into complex movements. However, stability and repeatability were still unmet requirements in multi-DoF upper limb systems; hence, I started by investigating different strategies to produce a more robust control. To do this, EMG signals were collected from trans-radial amputees using an array of up to six sensors placed over the skin. Secondly, I developed a vibrotactile system to implement haptic feedback to restore proprioception and create a bidirectional connection between the user and the prosthesis. Similarly, I implemented an object stiffness detection to restore tactile sensation able to connect the user with the external word. This closed-loop control between EMG and vibration feedback is essential to implementing a Bidirectional Body - Machine Interface to impact amputees’ daily life strongly. For each of these three activities: (i) implementation of robust pattern recognition control algorithms, (ii) restoration of proprioception, and (iii) restoration of the feeling of the grasped object's stiffness, I performed a study where data from healthy subjects and amputees was collected, in order to demonstrate the efficacy and usability of my implementations. In each study, I evaluated both the algorithms and the subjects’ ability to use the prosthesis by means of the F1Score parameter (offline) and the Target Achievement Control test-TAC (online). With this test, I analyzed the error rate, path efficiency, and time efficiency in completing different tasks. Main results. Among the several tested methods for Pattern Recognition, the Non-Linear Logistic Regression (NLR) resulted to be the best algorithm in terms of F1Score (99%, robustness), whereas the minimum number of electrodes needed for its functioning was determined to be 4 in the conducted offline analyses. Further, I demonstrated that its low computational burden allowed its implementation and integration on a microcontroller running at a sampling frequency of 300Hz (efficiency). Finally, the online implementation allowed the subject to simultaneously control the Hannes prosthesis DoFs, in a bioinspired and human-like way. In addition, I performed further tests with the same NLR-based control by endowing it with closed-loop proprioceptive feedback. In this scenario, the results achieved during the TAC test obtained an error rate of 15% and a path efficiency of 60% in experiments where no sources of information were available (no visual and no audio feedback). Such results demonstrated an improvement in the controllability of the system with an impact on user experience. Significance. The obtained results confirmed the hypothesis of improving robustness and efficiency of a prosthetic control thanks to of the implemented closed-loop approach. The bidirectional communication between the user and the prosthesis is capable to restore the loss of sensory functionality, with promising implications on direct translation in the clinical practice

Closed-loop prosthetic hand : understanding sensorimotor and multisensory integration under uncertainty.

To make sense of our unpredictable world, humans use sensory information streaming through billions of peripheral neurons. Uncertainty and ambiguity plague each sensory stream, yet remarkably our perception of the world is seamless, robust and often optimal in the sense of minimising perceptual variability. Moreover, humans have a remarkable capacity for dexterous manipulation. Initiation of precise motor actions under uncertainty requires awareness of not only the statistics of our environment but also the reliability of our sensory and motor apparatus. What happens when our sensory and motor systems are disrupted? Upper-limb amputees tted with a state-of-the-art prostheses must learn to both control and make sense of their robotic replacement limb. Tactile feedback is not a standard feature of these open-loop limbs, fundamentally limiting the degree of rehabilitation. This thesis introduces a modular closed-loop upper-limb prosthesis, a modified Touch Bionics ilimb hand with a custom-built linear vibrotactile feedback array. To understand the utility of the feedback system in the presence of multisensory and sensorimotor influences, three fundamental open questions were addressed: (i) What are the mechanisms by which subjects compute sensory uncertainty? (ii) Do subjects integrate an artificial modality with visual feedback as a function of sensory uncertainty? (iii) What are the influences of open-loop and closed-loop uncertainty on prosthesis control? To optimally handle uncertainty in the environment people must acquire estimates of the mean and uncertainty of sensory cues over time. A novel visual tracking experiment was developed in order to explore the processes by which people acquire these statistical estimators. Subjects were required to simultaneously report their evolving estimate of the mean and uncertainty of visual stimuli over time. This revealed that subjects could accumulate noisy evidence over the course of a trial to form an optimal continuous estimate of the mean, hindered only by natural kinematic constraints. Although subjects had explicit access to a measure of their continuous objective uncertainty, acquired from sensory information available within a trial, this was limited by a conservative margin for error. In the Bayesian framework, sensory evidence (from multiple sensory cues) and prior beliefs (knowledge of the statistics of sensory cues) are combined to form a posterior estimate of the state of the world. Multiple studies have revealed that humans behave as optimal Bayesian observers when making binary decisions in forced-choice tasks. In this thesis these results were extended to a continuous spatial localisation task. Subjects could rapidly accumulate evidence presented via vibrotactile feedback (an artificial modality ), and integrate it with visual feedback. The weight attributed to each sensory modality was chosen so as to minimise the overall objective uncertainty. Since subjects were able to combine multiple sources of sensory information with respect to their sensory uncertainties, it was hypothesised that vibrotactile feedback would benefit prosthesis wearers in the presence of either sensory or motor uncertainty. The closed-loop prosthesis served as a novel manipulandum to examine the role of feed-forward and feed-back mechanisms for prosthesis control, known to be required for successful object manipulation in healthy humans. Subjects formed economical grasps in idealised (noise-free) conditions and this was maintained even when visual, tactile and both sources of feedback were removed. However, when uncertainty was introduced into the hand controller, performance degraded significantly in the absence of visual or tactile feedback. These results reveal the complementary nature of feed-forward and feed-back processes in simulated prosthesis wearers, and highlight the importance of tactile feedback for control of a prosthesis

Haptics: Science, Technology, Applications

This open access book constitutes the proceedings of the 13th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2022, held in Hamburg, Germany, in May 2022. The 36 regular papers included in this book were carefully reviewed and selected from 129 submissions. They were organized in topical sections as follows: haptic science; haptic technology; and haptic applications

Prosthetic Control and Sensory Feedback for Upper Limb Amputees

Hand amputation could dramatically degrade the life quality of amputees. Many amputees use prostheses to restore part of the hand functions. Myoelectric prosthesis provides the most dexterous control. However, they are facing high rejection rate. One of the reasons is the lack of sensory feedback. There is a need for providing sensory feedback for myoelectric prosthesis users. It can improve object manipulation abilities, enhance the perceptual embodiment of myoelectric prostheses and help reduce phantom limb pain. This PhD work focuses on building bi-directional prostheses for upper limb amputees. In the introduction chapter, first, an overview of upper limb amputee demographics and upper limb prosthesis is given. Then the human somatosensory system is briefly introduced. The next part reviews invasive and non-invasive sensory feedback methods reported in the literature. The rest of the chapter describes the motivation of the project and the thesis organization. The first step to build a bi-directional prostheses is to investigate natural and robust multifunctional prosthetic control. Most of the commerical prostheses apply non-pattern recognition based myoelectric control methods, which offers only limited functionalities. In this thesis work, pattern recognition based prosthetic control employing three commonly used and representative machine learning algorithms is investigated. Three datasets involving different levels of upper arm movements are used for testing the algorithm effectiveness. The influence of time-domain features, window and increment sizes, algorithms, and post-processing techniques are analyzed and discussed. The next three chapters address different aspects of providing sensory feedback. The first focus of sensory feedback process is the automatic phantom map detection. Many amputees have referred sensation from their missing hand on their residual limbs (phantom maps). This skin area can serve as a target for providing amputees with non-invasive tactile sensory feedback. One of the challenges of providing sensory feedback on the phantom map is to define the accurate boundary of each phantom digit because the phantom map distribution varies from person to person. Automatic phantom map detection methods based on four decomposition support vector machine algorithms and three sampling methods are proposed. The accuracy and training/ classification time of each algorithm using a dense stimulation array and two coarse stimulation arrays are presented and compared. The next focus of the thesis is to develop non-invasive tactile display. The design and psychophysical testing results of three types of non-invasive tactile feedback arrays are presented: two with vibrotactile modality and one with multi modality. For vibrotactile, two types of miniaturized vibrators: eccentric rotating masses (ERMs) and linear resonant actuators (LRAs) were first tested on healthy subjects and their effectiveness was compared. Then the ERMs are integrated into a vibrotactile glove to assess the feasibility of providing sensory feedback for unilateral upper limb amputees on the contralateral hand. For multimodal stimulation, miniature multimodal actuators integrating servomotors and vibrators were designed. The actuator can be used to deliver both high-frequency vibration and low-frequency pressures simultaneously. By utilizing two modalities at the same time, the actuator stimulates different types of mechanoreceptors and thus h

A vibrotactile display design for the feedback of external prosthesis sensory information to the amputee wearer

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2006.Includes bibliographical references (p. 60-64).This thesis documents the development of a vibrotactile display to be incorporated into a powered ankle-foot prosthesis. Although existing devices have addressed the need for tactile and proprioceptive feedback in external prostheses, there has not yet been an attempt to develop and clinically evaluate a comprehensive vibrotactile display and signaling schematic for use with an active myoelectric prosthesis. The development and evaluation of two different hardware solutions are presented including an array of vibrating pancake motors embedded into the exterior of a carbon fiber prosthetic socket and an array of vibrating pancake motors embedded into a silicone socket liner. Three haptic mappings were designed based on previous work in psychophysics, haptics, and HCI. These schematics include a spatial discrimination pattern, an amplitude modulated pattern, and a gap detection pattern. To assess the effectiveness of the system, lower-limb amputees were asked to learn the three haptic mappings and use the feedback system to control a virtual ankle to a desired ankle position using a physical knob interface. Results show an overall recognition rate of 85% for all three haptic mappings and error response averages ranging from 8.2 s to 11.6 s.(cont.) The high recognition rates and lack of variance between the mappings suggest that the three vibration parameters of spatial discrimination, amplitude modulation, and gap detection may be successfully used to represent different ankle parameters. However, the overall successful integration of the vibrotactile display ultimately depends on the interaction between the components of the whole prosthetic system.by Andrea W. Chew.S.M

Designing sensory feedback approaches for restoring touch and position feedback in upper limb amputees

Upper limb amputation disrupts most daily activities and reduces the quality of life of affected individuals. Building a suitable prosthetic limb, which can restore at least some of the lost capabilities, is a goal which has been pursued for centuries. In the last few decades, our rapidly expanding understanding of the human nervous system has unlocked impressive advances in artificial limbs. Today, commercial prosthetic hands can be controlled intuitively through voluntary muscle contractions. Nevertheless, despite leaps in the quality of modern prostheses, sensory feedback remains one of the major omissions, forcing users to rely on vision to accomplish basic tasks, such as holding a plastic cup without crushing it. Several sensory feedback strategies have recently been developed to restore tactile and proprioceptive feedback to amputees, demonstrating benefits in important areas, such as higher functional performance and increases in the sense of prosthesis ownership. Sensory feedback strategies can be distinguished based on whether the sensation they restore matches the quality (homologous feedback) or the location (somatotopic feedback) of the original sensation. Despite promising results, somatotopic tactile feedback strategies often result in unnatural sensations (e.g. electricity). Furthermore, restoration of more than a single sensory modality is rarely reported, despite being necessary to create artificial limbs capable of delivering realistic sensorimotor experiences during use. In this work, I proposed three novel and complementary strategies to improve sensory feedback restoration in upper limb prostheses. I begin by describing a non-invasive transcutaneous electrical nerve stimulation (TENS) approach aimed at restoring somatotopic tactile sensations, which is potentially applicable to all trans-radial amputees. This stimulation strategy was shown to lead to high performance during functional tasks, and compared favorably to more invasive approaches, despite a few key differences. Considering that there is no such thing as a one-size-fits-all solution for amputees, I concluded that TENS represents a viable alternative to invasive systems, especially in cases where an implant is not possible or desirable. In the second part, I proposed a sensory substitution approach to multimodal feedback, which delivered somatotopic tactile and remapped proprioceptive feedback simultaneously. This stimulation strategy relied entirely on implantable electrodes, simplifying the overall system by delivering two streams of sensory information with the same device. Using this feedback system, two amputees were able to perform interesting functional tasks, such as understanding the size and compliance of various objects, with high accuracy. Finally, I proposed a novel stimulation technique for sensory feedback designed to desynchronize induced neural activity during electrical stimulation, leading to more biomimetic patterns of activity. I discussed how this strategy could be combined with the results obtained in a recent study which I contributed to, in which we demonstrated that a model based encoding strategy resulted in more natural sensations of touch. This thesis provides evidence that advances in electrical stimulation protocols can lead to more capable prosthetic limbs. These new methods enable the delivery of multimodal, biomimetic sensory feedback and will help bridge the gap between scientific discovery and clinical translation