A systematic approach to the design and characterization of a smart insole for detecting vertical ground reaction force (vGRF) in gait analysis

Gait analysis is a systematic study of human locomotion, which can be utilized in various applications, such as rehabilitation, clinical diagnostics and sports activities. The various limitations such as cost, non-portability, long setup time, post-processing time etc., of the current gait analysis techniques have made them unfeasible for individual use. This led to an increase in research interest in developing smart insoles where wearable sensors can be employed to detect vertical ground reaction forces (vGRF) and other gait variables. Smart insoles are flexible, portable and comfortable for gait analysis, and can monitor plantar pressure frequently through embedded sensors that convert the applied pressure to an electrical signal that can be displayed and analyzed further. Several research teams are still working to improve the insoles' features such as size, sensitivity of insoles sensors, durability, and the intelligence of insoles to monitor and control subjects' gait by detecting various complications providing recommendation to enhance walking performance. Even though systematic sensor calibration approaches have been followed by different teams to calibrate insoles' sensor, expensive calibration devices were used for calibration such as universal testing machines or infrared motion capture cameras equipped in motion analysis labs. This paper provides a systematic design and characterization procedure for three different pressure sensors: force-sensitive resistors (FSRs), ceramic piezoelectric sensors, and flexible piezoelectric sensors that can be used for detecting vGRF using a smart insole. A simple calibration method based on a load cell is presented as an alternative to the expensive calibration techniques. In addition, to evaluate the performance of the different sensors as a component for the smart insole, the acquired vGRF from different insoles were used to compare them. The results showed that the FSR is the most effective sensor among the three sensors for smart insole applications, whereas the piezoelectric sensors can be utilized in detecting the start and end of the gait cycle. This study will be useful for any research group in replicating the design of a customized smart insole for gait analysis. 2020 by the authors. Licensee MDPI, Basel, Switzerland.This research was partially funded by Qatar National Research Foundation (QNRF), grant number NPRP12S-0227-190164 and Research University Grant DIP-2018-017. The publication of this article was funded by the Qatar National Library. The authors would like to thank Engr. Ayman Ammar, Electrical Engineering, Qatar University for helping in printing the printed circuit boards (PCBs). This research was partially funded by Qatar National Research Foundation (QNRF), grant number NPRP12S-0227-190164 and Research University Grant DIP-2018-017. The publication of this article was funded by the Qatar National Library.Scopu

Low-Cost Sensors and Biological Signals

Many sensors are currently available at prices lower than USD 100 and cover a wide range of biological signals: motion, muscle activity, heart rate, etc. Such low-cost sensors have metrological features allowing them to be used in everyday life and clinical applications, where gold-standard material is both too expensive and time-consuming to be used. The selected papers present current applications of low-cost sensors in domains such as physiotherapy, rehabilitation, and affective technologies. The results cover various aspects of low-cost sensor technology from hardware design to software optimization

Homecare Robotic Systems for Healthcare 4.0: Visions and Enabling Technologies

Powered by the technologies that have originated from manufacturing, the fourth revolution of healthcare technologies is happening (Healthcare 4.0). As an example of such revolution, new generation homecare robotic systems (HRS) based on the cyber-physical systems (CPS) with higher speed and more intelligent execution are emerging. In this article, the new visions and features of the CPS-based HRS are proposed. The latest progress in related enabling technologies is reviewed, including artificial intelligence, sensing fundamentals, materials and machines, cloud computing and communication, as well as motion capture and mapping. Finally, the future perspectives of the CPS-based HRS and the technical challenges faced in each technical area are discussed

Human and Biological Skin-Inspired Electronic Skins for Advanced Sensory Functions and Multifunctionality

Department of Energy Engineering (Energy Engineering)The electronic skin (e-skin) technology is an exciting frontier to drive next generation of wearable electronics owing to its high level of wearability to curved human body, enabling high accuracy to harvest information of users and their surroundings. Altough various types of e-skins, based on several signal-transduction modes, including piezoresistive, capacitive, piezoelectric, triboelectric modes, have been developed, their performances (i.e. sensitivity, working range, linearity, multifunctionality, etc.) should be improved for the wearable applications. Recently, biomimicry of the human and biological skins has become a great inspiration for realizing novel wearable e-skin systems with exceptional multifunctionality as well as advanced sensory functions. As an ideal sensory organ, tactile sensing capabilities of human skin was emulated for the development of e-skins with enhanced sensor performances. In particular, the unique geometry and systematic sensory system of human skin have driven new opportunities in multifunctional and highly sensitive e-skin applications. In addition, extraordinary architectures for protection, locomotion, risk indication, and camouflage in biological systems provide great possibilities for second skin applications on user-interactive, skin-attachable, and ultrasensitive e-skins, as well as soft robots. Benefitting from their superior perceptive functions and multifunctionality, human and biological skins-inspired e-skins can be considered to be promising candidates for wearable device applications, such as body motion tracking, healthcare devices, acoustic sensor, and human machine interfaces (HMI). This thesis covers our recent studies about human and biological skin-inspired e-skins for advanced sensory functions and multifunctionality. First, chapter 1 highlights various types of e-skins and recent research trends in bioinspired e-skins mimicking perceptive features of human and biological skins. In chapter 2, we demonstrate highly sensitive and tactile-direction-sensitive e-skin based on human skin-inspired interlocked microdome structures. Owing to the stress concentration effect, the interlocked e-skin experiences significant change of contact area between the interlocked microdomes, resulting in high pressure sensitivity. In addition, because of the different deformation trends between microstructures in mutual contact, the interlocked e-skin can differentiate and decouple sensor signals under different directional forces, such as pressure, tensile strain, shear, and bending. In chapter 3, interlocked e-skins were designed with multilayered geometry. Although interlocked e-skin shows highly sensitive pressure sensing performances, their pressure sensing range is narrow and pressure sensitivity continuously decreases with increasing pressure level. The multilayer interlocked microdome geometry can enhance the pressure-sensing performances of e-skins, such as sensitivity, working range, and linearity. As another approach of e-skin with multilayered geometry, we demonstrate multilayered e-skin based on conductivity-gradient conductive materials in chapter 4. The conducive polymer composites with different conductivity were coated on the microdome pattern and designed as interlocked e-skin with coplanar electrode design, resulting in exceptionally high pressure-sensing performances compared with previous literatures. In chapter 5, inspired by responsive color change in biological skins, we developed mechanochromic e-skin with a hierarchical nanoparticle-in-micropore architecture. The novel design of hierarchical structure enables effective stress concentration at the interface between nanoparticle and porous structure, resulting in impressive color change under mechanical stimuli. In chapter 6, we emulate ultrahigh temperature sensitivity of human and snake skin for temperature-sensitive e-skin. The thermoresponsive composite based on semi-crystalline polymer, temperature sensor shows ultrahigh temperature sensitivity near the melting point of semi-crystalline polymer. In addition, integration of thermochromic composite, mimicking biological skins, enables dual-mode temperature sensors by electrical and colorimetric sensing capabilities. Finally, in chapter 7, we summarize this thesis along with future perspective that should be considered for next-generation e-skin electronics. Our e-skins, inspired by human and biological skin, can provide a new paradigm for realizing novel wearable electronic systems with exceptional multifunctionality as well as advanced sensory functions.clos

Advance in Energy Harvesters/Nanogenerators and Self-Powered Sensors

This reprint is a collection of the Special Issue "Advance in Energy Harvesters/Nanogenerators and Self-Powered Sensors" published in Nanomaterials, which includes one editorial, six novel research articles and four review articles, showcasing the very recent advances in energy-harvesting and self-powered sensing technologies. With its broad coverage of innovations in transducing/sensing mechanisms, material and structural designs, system integration and applications, as well as the timely reviews of the progress in energy harvesting and self-powered sensing technologies, this reprint could give readers an excellent overview of the challenges, opportunities, advancements and development trends of this rapidly evolving field

Biomechatronics: Harmonizing Mechatronic Systems with Human Beings

This eBook provides a comprehensive treatise on modern biomechatronic systems centred around human applications. A particular emphasis is given to exoskeleton designs for assistance and training with advanced interfaces in human-machine interaction. Some of these designs are validated with experimental results which the reader will find very informative as building-blocks for designing such systems. This eBook will be ideally suited to those researching in biomechatronic area with bio-feedback applications or those who are involved in high-end research on manmachine interfaces. This may also serve as a textbook for biomechatronic design at post-graduate level

Hybrid pesponse pressure sensors as an electronic skin for bio-sensing and soft robotics

Soft pressure sensors are critical components of e-skins, which are playing an increasingly significant role in two burgeoning fields: soft robotics and bio-electronics. Capacitive pressure sensors are popular given their mechanical flexibility, high sensitivity, and signal stability. After two decades of rapid development, e-skins based on soft capacitive pressure sensors are able to achieve human-skin-like softness and sensitivity. However, there remain two major roadblocks in the way of the practical application of soft capacitive pressure sensors: 1) the decay of sensitivity with increased pressure and 2) the coupled response between in-plane stretch and out-of-plane pressure. This dissertation aims to tackle the two critical challenges. To increase the sensitivity of a capacitive pressure sensor, past research has mostly focused on developing dielectric layers with surface/porous structures or higher dielectric constants. However, such strategies have only been effective in improving sensitivities at low pressure ranges (e.g. up to 3 kPa). To overcome this well-known obstacle, I devised a flexible hybrid response pressure sensor (HRPS) composed of an electrically conductive porous nanocomposite (PNC) laminated with an ultrathin dielectric layer. Using a nickel foam template, the PNC was fabricated with carbon nanotubes (CNT) doped Ecoflex to be 86% porous and electrically conductive. The PNC exhibits hybrid piezoresistive and piezocapacitive responses, resulting in significantly enhanced sensitivities (i.e., more than 400%) over wide pressure ranges, from 3.13 kPa⁻¹ within 0-1 kPa to 0.43 kPa⁻¹ within 30-50 kPa. The effect of the hybrid responses was differentiated from the effect of porosity or high dielectric constants by comparing the HRPS with its purely piezocapacitive counterparts. Fundamental understanding of the HRPS and the prediction of optimal CNT doping were achieved through simplified analytical models. Second, coupled pressure and stretching responses disable capacitive sensors to differentiate out-of-plane and in-plane inputs. Due to this critical limitation, intrinsically stretchable and accurate capacitive pressure sensors have not been successfully demonstrated, while other types of soft sensors have already achieved stretchability beyond flexibility. To discriminate the compression and stretching responses, I proposed a stretchable hybrid response pressure sensor (SHRPS). SHRPS is a stretchable version of HRPS, whose sensitive pressure response trivializes the stretching response and enables the SHRPS to accurately read applied pressure even under stretching. Analytical models for conventional capacitive pressure sensors, HRPS and SHRPS have been developed and provide fundamental electromechanical understanding for the difference among the three. As a demonstration, a 3 x 3 SHPRS array has been glued to an inflatable manipulator which is capable of diverse tasks such as pulse palpation and object grabbing given the tunable inflation. A perspective for the future directions of HRPS is provided at the end of the dissertation.Mechanical Engineerin

A data-driven method to reduce excessive contact pressure of hand orthosis using a soft sensor skin

Discomfort under customised hand orthosis has been commonly reported in clinics due to excessive contact pressures, leading to low patient adherence and decreased effectiveness of orthosis. However, the current orthosis adjustment by clinicians to reduce pressures based upon subjective feedback from patients is inefficient and prone to variability. Therefore, a quantitative method to guide orthosis adjustment was proposed here by developing a data-driven method. Firstly, Verbal Protocol Analysis was employed to convert the implicit process of orthosis customisation into working models of clinicians. Relevant data to inform a new solution development to reduce excessive contact pressure were extracted from the working models in terms of time consumption and iterations of tasks. Secondly, a new soft sensor skin with strategically placed sensing units to measure static contact pressures under hand orthoses was developed. Finite element simulations were conducted to reveal the required contact pressure range (0.02 – 0.078 MPa) and the distribution of relatively high pressures in 12 key areas. A new fabrication method was proposed to produce the sensor skin, which was then characterised and tested on the subject. The results show that the sensor unit has a pressure range from 0.01 MPa to 0.1 MPa with the maximum repeatability error of 6.4% at 0.014 MPa, and the maximum measurement error of 8.26% at 0.023 MPa. Thirdly, a new method was proposed to predict contact pressures associated with the moderate level of discomfort at critical spots under hand orthoses. 40 patients were recruited to collect contact pressures under two types of orthoses using the sensor skin, and their discomfort perceptions were measured with a categorical scale. Based on these data, artificial neural networks for five identified critical spots on the hand were built to predict pressure thresholds that clinicians can use to adjust orthoses, thus reducing excessive contact pressures. The neural networks show satisfactory prediction accuracy with R2 values over 0.89 of regression between network outputs and measurements. Collectively, this thesis proposed a novel method for clinicians to adjust orthoses quantitatively and reduce the need for subjective assessment for patients. It provided a platform to further investigate the pressure for patients with other conditions.Open Acces

Wearable and BAN Sensors for Physical Rehabilitation and eHealth Architectures

The demographic shift of the population towards an increase in the number of elderly citizens, together with the sedentary lifestyle we are adopting, is reflected in the increasingly debilitated physical health of the population. The resulting physical impairments require rehabilitation therapies which may be assisted by the use of wearable sensors or body area network sensors (BANs). The use of novel technology for medical therapies can also contribute to reducing the costs in healthcare systems and decrease patient overflow in medical centers. Sensors are the primary enablers of any wearable medical device, with a central role in eHealth architectures. The accuracy of the acquired data depends on the sensors; hence, when considering wearable and BAN sensing integration, they must be proven to be accurate and reliable solutions. This book is a collection of works focusing on the current state-of-the-art of BANs and wearable sensing devices for physical rehabilitation of impaired or debilitated citizens. The manuscripts that compose this book report on the advances in the research related to different sensing technologies (optical or electronic) and body area network sensors (BANs), their design and implementation, advanced signal processing techniques, and the application of these technologies in areas such as physical rehabilitation, robotics, medical diagnostics, and therapy