Haptic wearables as sensory replacement, sensory augmentation and trainer - a review

Sensory impairments decrease quality of life and can slow or hinder rehabilitation. Small, computationally powerful electronics have enabled the recent development of wearable systems aimed to improve function for individuals with sensory impairments. The purpose of this review is to synthesize current haptic wearable research for clinical applications involving sensory impairments. We define haptic wearables as untethered, ungrounded body worn devices that interact with skin directly or through clothing and can be used in natural environments outside a laboratory. Results of this review are categorized by degree of sensory impairment. Total impairment, such as in an amputee, blind, or deaf individual, involves haptics acting as sensory replacement; partial impairment, as is common in rehabilitation, involves haptics as sensory augmentation; and no impairment involves haptics as trainer. This review found that wearable haptic devices improved function for a variety of clinical applications including: rehabilitation, prosthetics, vestibular loss, osteoarthritis, vision loss and hearing loss. Future haptic wearables development should focus on clinical needs, intuitive and multimodal haptic displays, low energy demands, and biomechanical compliance for long-term usage

Design Principles for FES Concept Development

© Cranfield University 2013. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright owner.A variety of pathologies can cause injury to the spinal cord and hinder movement. A range of equipment is available to help spinal injury sufferers move their affected limbs. One method of rehabilitation is functional electrical stimulation (FES). FES is a technique where small electrical currents are applied to the surface of the user’s legs to stimulate the muscles. Studies have demonstrated the benefits of using this method and it has also been incorporated into a number of devices. The aim of the project was to produce a number of designs for a new device that uses FES technology. The project was completed in conjunction with an industrial partner. A review of the literature and consultation with industrial experts suggested a number of ways current devices could be improved. These included encouraging the user to lean forwards while walking and powering the device using a more ergonomic method. A group of designers were used to produce designs that allowed the user to walk with a more natural gait and avoided cumbersome power packs. The most effective of these designs were combined to form one design that solved both problems. A 3-dimensional model of this design was simulated using computer-aided design software. Groups of engineers, scientists and consumers were also invited to provide input on how a new device should function. Each of these groups provided a design that reflected their specific needs, depending on their experience with similar technology. Low level prototypes were produced of these designs. A group of designers were also used to design concepts for a functional electrical stimulation device based on an introduction given by industry experts. Each of the designs was presented to experienced professionals to obtain feedback. A set of guidelines were also produced during the project that instructed how to create the designs

Instrumented shoes for daily activity monitoring in healthy and at risk populations

Daily activity reflects the health status of an individual. Ageing and disease drastically affect all dimensions of mobility, from the number of active bouts to their duration and intensity. Performing less activity leads to muscle deterioration and further weakness that could lead to increased fall risk. Gait performance is also affected by ageing and could be detrimental for daily mobility. Therefore, activity monitoring in older adults and at risk persons is crucial to obtain relevant quantitative information about daily life performance. Activity evaluation has mainly been established through questionnaires or daily logs. These methods are simple but not sufficiently accurate and are prone to errors. With the advent of microelectromechanical systems (MEMS), the availability of wearable sensors has shifted activity analysis towards ambulatory monitoring. In particular, inertial measurement units consisting of accelerometers and gyroscopes have shown to be extremely relevant for characterizing human movement. However, monitoring daily activity requires comfortable and easy to use systems that are strategically placed on the body or integrated in clothing to avoid movement hindrance. Several research based systems have employed multiple sensors placed at different locations, capable of recognizing activity types with high accuracy, but not comfortable for daily use. Single sensor systems have also been used but revealed inaccuracies in activity recognition. To this end, we propose an instrumented shoe system consisting of an inertial measurement unit and a pressure sensing insole with all the sensors placed at the shoe/foot level. By measuring the foot movement and loading, the recognition of locomotion and load bearing activities would be appropriate for activity classification. Furthermore, inertial measurement units placed on the foot can perform detailed gait analysis, providing the possibility of characterizing locomotion. The system and dedicated activity classification algorithms were first designed, tested and validated during the first part of the thesis. Their application to clinical rehabilitation of at risk persons was demonstrated over the second part. In the first part of the thesis, the designed instrumented shoes system was tested in standardized conditions with healthy elderly subjects performing a sequence of structured activities. An algorithm based on movement biomechanics was built to identify each activity, namely sitting, standing, level walking, stairs, ramps, and elevators. The rich array of sensors present in the system included a 3D accelerometer, 3D gyroscope, 8 force sensors, and a barometer allowing the algorithm to reach a high accuracy in classifying different activity types. The tuning parameters of the algorithm were shown to be robust to small changes, demonstrating the suitability of the algorithm to activity classification in older adults. Next, the system was tested in daily life conditions on the same elderly participants. Using a wearable reference system, the concurrent validity of the instrumented shoes in classifying daily activity was shown. Additionally, daily gait metrics were obtained and compared to the literature. Further insight into the relationship between some gait parameters as well as a global activity metric, the activity âcomplexityâ, was discussed. Participants positively rated their comfort while using the system... (Please refer to thesis for full abstract

Foundations of space biology and medicine. Volume 2, book 1: Ecological and physiological bases of space biology and medicine

Barometric pressure, gas composition, toxicity, and thermal exchange of spacecraft cabin atmospheres are discussed. Effects of gravitation, acceleration, weightlessness, noise, and vibration on human behavior and performance during space flight are also described

Smart Sensors for Healthcare and Medical Applications

This book focuses on new sensing technologies, measurement techniques, and their applications in medicine and healthcare. Specifically, the book briefly describes the potential of smart sensors in the aforementioned applications, collecting 24 articles selected and published in the Special Issue “Smart Sensors for Healthcare and Medical Applications”. We proposed this topic, being aware of the pivotal role that smart sensors can play in the improvement of healthcare services in both acute and chronic conditions as well as in prevention for a healthy life and active aging. The articles selected in this book cover a variety of topics related to the design, validation, and application of smart sensors to healthcare

Design and Development of Biofeedback Stick Technology (BfT) to Improve the Quality of Life of Walking Stick Users

Biomedical engineering has seen a rapid growth in recent times, where the aim to facilitate and equip humans with the latest technology has become widespread globally. From high-tech equipment ranging from CT scanners, MRI equipment, and laser treatments, to the design, creation, and implementation of artificial body parts, the field of biomedical engineering has significantly contributed to mankind. Biomedical engineering has facilitated many of the latest developments surrounding human mobility, with advancement in mobility aids improving human movement for people with compromised mobility either caused by an injury or health condition. A review of the literature indicated that mobility aids, especially walking sticks, and appropriate training for their use, are generally prescribed by allied health professionals (AHP) to walking stick users for rehabilitation and activities of daily living (ADL). However, feedback from AHP is limited to the clinical environment, leaving walking stick users vulnerable to falls and injuries due to incorrect usage. Hence, to mitigate the risk of falls and injuries, and to facilitate a routine appraisal of individual patient’s usage, a simple, portable, robust, and reliable tool was developed which provides the walking stick users with real-time feedback upon incorrect usage during their activities of daily living (ADL). This thesis aimed to design and develop a smart walking stick technology: Biofeedback stick technology (BfT). The design incorporates the approach of patient and public involvement (PPI) in the development of BfT to ensure that BfT was developed as per the requirements of walking stick users and AHP recommendations. The newly developed system was tested quantitatively for; validity, reliability, and reproducibility against gold standard equipment such as the 3D motion capture system, force plates, optical measurement system for orientation, weight bearing, and step count. The system was also tested qualitatively for its usability by conducting semi-informal interviews with AHPs and walking stick users. The results of these studies showed that the newly developed system has good accuracy, reported above 95% with a maximum inaccuracy of 1°. The data reported indicates good reproducibility. The angles, weight, and steps recorded by the system during experiments are within the values published in the literature. From these studies, it was concluded that, BfT has the potential to improve the lives of walking stick users and that, with few additional improvements, appropriate approval from relevant regulatory bodies, and robust clinical testing, the technology has a huge potential to carve its way to a commercial market

Wrist-Worn Accelerometer Measures of Activity by People with Parkinson's Attending Dance Classes

There has been increasing interest from researchers, dance artists and health professionals regarding the physical and psychological benefits of dance for people with Parkinson’s, particularly as a possible adjunct therapeutic intervention to medication. Studies examining the effect of dance on health outcomes such as parameters of movement have typically used brief, snap-shot assessments that limit understanding of movement to the timeframe in which the test or self-report measure is administered. Furthermore, such measures may be influenced by mood and cognitive capabilities. Accelerometry has been used to study the effect of various health interventions on the physical activity levels of people with Parkinson’s, but the types of activities studied have not yet included dance. The present thesis aimed to investigate the application of wrist-worn accelerometers as an objective measure of movement to dance for Parkinson’s research. Specifically, this work intended to advance current knowledge regarding the uses of accelerometers with people with Parkinson’s by exploring i) the feasibility of using wrist-worn devices to measure movement parameters during and after participation in a dance class, ii) participant adherence to a wrist-worn device , iii) the validity of wrist-placement in the assessment of movement, iv) the usefulness of volume of movement as a single summary metric of movement, and v) how values for the assessment of physical activity intensity derived from a wrist-worn accelerometer compare to previously published values obtained from other device placements. A series of exploratory studies were undertaken to address these aims. The first study addressed the gap in the literature regarding the use of accelerometry in the measurement of the level and pattern of movement made by people with and without Parkinson’s during a dance class. Participant triads, consisting of one person with Parkinson’s, an age-matched control and a young adult attending the same class at the University of Hertfordshire, wore a GENEActiv accelerometer on their wrist for an hour dance session and the following hour rest session. The results showed that the accelerometers accurately tracked the movement of the participant triads and detected between-group differences across all triads, such that young adults were significantly more active over the two hours compared to the participants with Parkinson’s and age-matched controls. The second study examined whether an objective measure of movement, derived from the accelerometers, supported the anecdotal reports of people with Parkinson’s of maintained levels of movement during the hours and days following attendance to a dance class. To this end, people with Parkinson’s and age-matched dancers (PD-D and AM-D, respectively) were asked to wear an accelerometer on their wrist over six consecutive days following attendance to a class, a free-living setting, and on a week when they did not attend a class. Accelerometer-derived movement and sleep metrics were compared between these two groups and to a separate control group of people with Parkinson’s who had never attended dance classes (PD-C). All participants were compliant with wearing the accelerometer over the consecutive days and very few removed the device. No significant differences were found between participant groups in terms of volume of movement and sleep quality. Though non-significant, PD-Ds and AM-Ds were 7% and 10% less physically active, respectively, on a Friday afternoon on a no-dance week compared to a dance week. No significant difference was found when movement was examined as a daily average, indicating that if there is an effect of dance on movement, it is likely to be short-lived. The final study focused on the development of values that can be used to interpret raw acceleration data derived from wrist-worn accelerometers in terms of physical activity intensity levels, specifically for use with people with Parkinson’s. Volume of movement (derived from a wrist, hip and ankle-worn device) and physiological energy expenditure (derived from a spiroergometry device) were calculated for people with Parkinson’s and age-matched controls as they undertook a variety of exercises and household activities in a sports laboratory. Corroborating the findings of previous research, the results showed that volume of movement derived from a wrist-worn device significantly predicted energy expenditure, but the addition of a second hip-worn accelerometer increased accuracy. Though no differences were found between the participant groups for volume of movement and energy expenditure, people with Parkinson’s rated all activities as significantly more exerting. This finding indicates that physiological exertion was similar between the two groups and that the symptoms of Parkinson’s may play a role in perceived exertion. Taken together, these studies demonstrate that wrist-worn accelerometers are acceptable and sensitive devices that can be used to investigate the engagement of people with and without Parkinson’s in activities such as dance. Volume of movement as an accelerometer-derived outcome is useful when physical activity is monitored under observable and predictable conditions, however future exploratory studies should consider incorporating a measure of physical activity intensity to further interpret acceleration data in light of government physical activity guidelines, particularly when monitoring movement in a free-living context