A Triple-Mode Flexible E-Skin Sensor Interface for Multi-Purpose Wearable Applications

This study presents a flexible wireless electronic skin (e-skin) sensor system that includes a multi-functional sensor device, a triple-mode reconfigurable readout integrated circuit (ROIC), and a mobile monitoring interface. The e-skin device's multi-functionality is achieved by an interlocked micro-dome array structure that uses a polyvinylidene fluoride and reduced graphene oxide (PVDF/RGO) composite material that is inspired by the structure and functions of the human fingertip. For multi-functional implementation, the proposed triple-mode ROIC is reconfigured to support piezoelectric, piezoresistance, and pyroelectric interfaces through single-type e-skin sensor devices. A flexible system prototype was developed and experimentally verified to provide various wireless wearable sensing functions-including pulse wave, voice, chewing/swallowing, breathing, knee movements, and temperature-while their real-time sensed data are displayed on a smartphone

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

Multifunctional wearable epidermal device for physiological signal monitoring in sleep study

Sleep is the essential part of life. Thousands of people are suffering from different kinds sleep disorders. Clinical diagnosing and treating for such disorders are costly, painful and quite sluggish. To reach the demand many commercial products are into the market to encourage home based sleep studies using portable devices. These portable devices are limited in use, cannot be handled easily and quite costly. Advancements in technology miniaturized these portable devices to wearable devices to make them convenient and economical. Elastic, soft and thin silicon membrane with physical properties well matched with that of the epidermis provides conformal and robust contact with the skin. Integration of an elastic and flexible electronics to such a membrane provides an epidermal electronic system (EES) that can enhance the robustness in operation for electrophysiological signal measurement. Biocompatible and non-invasive over the skin are the advantages of this class of technology that lie beyond those available with conventional, point-contact electrode interfaces to the skin. Recording of various long-term physiological signals relevant in various sleep studies can be performed using this multifunctional device. Optimized design of EES for monitoring various physiological signals like surface electroencephalography (EEG), electrooculography (EOG) and electromyography (EMG) are presented in this project --Abstract, page iii

Design, development and characterisation of piezoresistive and capacitive polymeric pressure sensors for use in compression hosiery

The work in this thesis was focused in developing a flexible and cost-effective pressure sensor capable of detecting pressure variations within the low working range (0-6kPa) of compression hosiery. For this cause, both piezoresistive and capacitive pressure sensors were developed and characterised, utilising conductive and non-conductive polymeric elements to sense compressive loads. In the first case, the developed piezoresistive sensor is composed of a conductive filler - polymer composite, with a force-dependent conductivity, encapsulated in between a structured and unstructured configuration of electrodes. Initially, as the sensing element of the sensor a multi-walled carbon nanotubes-polydimethylsiloxane (MWCNT-PDMS) composite was tested. A fabrication process is also proposed for developing the MWCNT-PDMS composite which involves a series of successive direct ultrasonications and shear mixing in order to disperse the two constituents of the composite, with the use of an organic solvent. Developing the composite over a range of different filler concentrations revealed a sharp step-like conductivity behaviour, typical amongst percolating composites. The MWCNT-PDMS sensor exhibited a positive piezoresistive response when subjected to compression, which was substantially enhanced when structured electrode layers were utilised. A Quantum Tunnelling Composite (QTC) material was also tested as the sensing material, which displays a large negative piezoresistive response when deformed. The QTC pressure sensor exhibited an improved performance, which was similarly significantly increased when a structured electrode was employed. In the second case, a parallel-plate capacitive pressure sensor was developed and characterised, which successfully provided a pressure sensitivity within the working range of compression hosiery. The sensor employs an ultra-thin PDMS blend film, with tuneable Young’s modulus, as the dielectric medium of the capacitor, bonded in between two rigid copper-coated glass layers. A casting process is also presented, involving the use of a sacrificial mould, in order to pattern the polymeric film with a micro-pillar structure to assist the deformation of the medium under compressive loads. The performance of the sensor with regards to the polymeric film thickness, structure and mechanical softness was explored. Overall, the combination of an ultra-thin dielectric medium with a very low Young’s modulus and a microstructured surface resulted in a capacitive pressure sensor with a good performance within the desired pressure regime

Multi-Biosignal Sensing Interface with Direct Sleep-Stage Classification

Department of Electrical EngineeringSleep is a time of mental and physical rest in a person???s daily cycle. It is an indispensable metabolic activity that helps the body grow and boosts immunity. Therefore, sleep disorders can cause illness in the body as well as just physical condition. Among these diseases are typically included rapid eye movement (REM) sleep behavior disorder, nocturnal enuresis, sleepwalking, etc., which can cause serious injury on sleep. Sleep disorders are a common disease. According to a survey, sleep deprivation and disability affect a significant part of the world???s population. It is a disease that affects tens of millions of people around the world. In general, treatment for sleep disorders checks the quality during sleep and prescribes various sleep diseases by checking the condition of sleep. Sleep quality and sleep disease are determined by the depth and time of the sleep phase. Therefore, the analysis and classification of the sleep stage are essential. According to the manual of the American Academy of Sleep Medicine (AASM), sleep stages are divided into five stages. Various methods for sleep analysis have been developed. Polysomnography (PSG), called the golden standard, is the most reliable measurement of sleep quality in hospitals for sleep disorders, but this conventional method requires the use of various human body signals, and it is difficult to access due to the complex interface and various electrodes. It is not economical because of its infrastructure, which does not lead to direct treatment of prospective patients. In addition, the conventional interface system process is not an integrated interface system. The integrated interface system refers to the integration of the interface in the measuring and analysis process. Conventional sensing and analysis take place on the instrument measuring the patient and on the analyst???s computer. Therefore, conventional treatments are not economical and make patient self-analysis difficult. Furthermore, this makes it difficult to increase the demand for prospective patients. This paper presents a multi-biosignal sensing interface system with direct sleep-stage classification. Unlike conventional systems, this work proposes an interface system that is an integrated interface system, measuring, and analysis based on the analog circuit and system. The proposed paper configures a multi-biosignal sensing interface consisting of single-channel EEG, EMG, and 2EoG. The multi-biosignal sensing readout integrated circuit (ROIC) collects analog signals from the electrodes and extracts features from the signal. The multi-biosignal sensing ROIC has a feature extraction stage that directly extracts the characteristic of sleep stages. The analog feature extraction stage consists of the optimized circuit for three multi-biosignal extracts the feature of each stage during sleep on the waveform. The extracted signal is scored by the rule-based decision tree sleep stage proposed by the micro controller unit (MCU). The multi-biosignal sensing ROIC can analyze the sleep stage through EEG, EMG, and 2EOG, and can simultaneously analyze four channels. The multi-biosignal sensing ROIC is implemented using a compensate metal-oxide-semiconductor 0.18um process. In addition, this system implements a low-power, integrated module for portable device configuration, and from this interface makes a smart headband for prospective patients. Depending on the purpose of use, it consists of 2 type paths, including raw data recording and analog feature extraction based direct sleep classification using decision tree algorithm. Finally, sleep stage scoring can be displayed, or raw data can be sent to the personal computer interface to increase accuracy. The sleep stage was verified by comparing the OpenBCI module-based MATLAB analysis using SVM with this system, and the result shows an overall accuracy of 74% for four sleep stages.clos

An Energy-Autonomous Smart Shirt employing wearable sensors for Users’ Safety and Protection in Hazardous Workplaces

none4siWearable devices represent a versatile technology in the IoT paradigm, enabling noninvasive and accurate data collection directly from the human body. This paper describes the development of a smart shirt to monitor working conditions in particularly dangerous workplaces. The wearable device integrates a wide set of sensors to locally acquire the user’s vital signs (e.g., heart rate, blood oxygenation, and temperature) and environmental parameters (e.g., the concentration of dangerous gas species and oxygen level). Electrochemical gas-monitoring modules were designed and integrated into the garment for acquiring the concentrations of CO, O2, CH2O, and H2S. The acquired data are wirelessly sent to a cloud platform (IBM Cloud), where they are displayed, processed, and stored. A mobile application was deployed to gather data from the wearable devices and forward them toward the cloud application, enabling the system to operate in areas where aWiFi hotspot is not available. Additionally, the smart shirt comprises a multisource harvesting section to scavenge energy from light, body heat, and limb movements. Indeed, the wearable device integrates several harvesters (thin-film solar panels, thermoelectric generators (TEGs), and piezoelectric transducers), a low-power conditioning section, and a 380 mAh LiPo battery to accumulate the recovered charge. Field tests indicated that the harvesting section could provide up to 216 mW mean power, fully covering the power requirements (P = 1.86 mW) of the sensing, processing, and communication sections in all considered conditions (3.54 mW in the worst-case scenario). However, the 380 mAh LiPo battery guarantees about a 16-day lifetime in the complete absence of energy contributions from the harvesting section.Special Issue “Innovative Materials, Smart Sensors and IoT-based Electronic Solutions for Wearable Applications”, https://www.mdpi.com/journal/applsci/special_issues/Materials_Sensors_Electronic_Solutions_Wearable_ApplicationsopenRoberto De Fazio, Abdel-Razzak Al-Hinnawi, Massimo De Vittorio, Paolo ViscontiDE FAZIO, Roberto; Al-Hinnawi, Abdel-Razzak; DE VITTORIO, Massimo; Visconti, Paol

Thermal and Mechanical Energy Harvesting Using Lead Sulfide Colloidal Quantum Dots

The human body is an abundant source of energy in the form of heat and mechanical movement. The ability to harvest this energy can be useful for supplying low-consumption wearable and implantable devices. Thermoelectric materials are usually used to harvest human body heat for wearable devices; however, thermoelectric generators require temperature gradient across the device to perform appropriately. Since they need to attach to the heat source to absorb the heat, temperature equalization decreases their efficiencies. Moreover, the electrostatic energy harvester, working based on the variable capacitor structure, is the most compatible candidate for harvesting low-frequency-movement of the human body. Although it can provide a high output voltage and high-power density at a small scale, they require an initial start-up voltage source to charge the capacitor for initiating the conversion process. The current methods for initially charging the variable capacitor suffer from the complexity of the design and fabrication process. In this research, a solution-processed photovoltaic structure was proposed to address the temperature equalization problem of the thermoelectric generators by harvesting infrared radiations emitted from the human body. However, normal photovoltaic devices have the bandgap limitation to absorb low energy photons radiated from the human body. In this structure, mid-gap states were intentionally introduced to the absorbing layer to activate the multi-step photon absorption process enabling electron promotion from the valence band to the conduction band. The fabricated device showed promising performance in harvesting low energy thermal radiations emitted from the human body. Finally, in order to increase the generated power, a hybrid structure was proposed to harvest both mechanical and heat energy sources available in the human body. The device is designed to harvest both the thermal radiation of the human body based on the proposed solution-processed photovoltaic structure and the mechanical movement of the human body based on an electrostatic generator. The photovoltaic structure was used to charge the capacitor at the initial step of each conversion cycle. The simple fabrication process of the photovoltaic device can potentially address the problem associated with the charging method of the electrostatic generators. The simulation results showed that the combination of two methods can significantly increase the harvested energy

Low Power Circuits for Smart Flexible ECG Sensors

Cardiovascular diseases (CVDs) are the world leading cause of death. In-home heart condition monitoring effectively reduced the CVD patient hospitalization rate. Flexible electrocardiogram (ECG) sensor provides an affordable, convenient and comfortable in-home monitoring solution. The three critical building blocks of the ECG sensor i.e., analog frontend (AFE), QRS detector, and cardiac arrhythmia classifier (CAC), are studied in this research. A fully differential difference amplifier (FDDA) based AFE that employs DC-coupled input stage increases the input impedance and improves CMRR. A parasitic capacitor reuse technique is proposed to improve the noise/area efficiency and CMRR. An on-body DC bias scheme is introduced to deal with the input DC offset. Implemented in 0.35m CMOS process with an area of 0.405mm2, the proposed AFE consumes 0.9W at 1.8V and shows excellent noise effective factor of 2.55, and CMRR of 76dB. Experiment shows the proposed AFE not only picks up clean ECG signal with electrodes placed as close as 2cm under both resting and walking conditions, but also obtains the distinct -wave after eye blink from EEG recording. A personalized QRS detection algorithm is proposed to achieve an average positive prediction rate of 99.39% and sensitivity rate of 99.21%. The user-specific template avoids the complicate models and parameters used in existing algorithms while covers most situations for practical applications. The detection is based on the comparison of the correlation coefficient of the user-specific template with the ECG segment under detection. The proposed one-target clustering reduced the required loops. A continuous-in-time discrete-in-amplitude (CTDA) artificial neural network (ANN) based CAC is proposed for the smart ECG sensor. The proposed CAC achieves over 98% classification accuracy for 4 types of beats defined by AAMI (Association for the Advancement of Medical Instrumentation). The CTDA scheme significantly reduces the input sample numbers and simplifies the sample representation to one bit. Thus, the number of arithmetic operations and the ANN structure are greatly simplified. The proposed CAC is verified by FPGA and implemented in 0.18m CMOS process. Simulation results show it can operate at clock frequencies from 10KHz to 50MHz. Average power for the patient with 75bpm heart rate is 13.34W

High Precision 3D Printing for Micro to Nano Scale Biomedical and Electronic Devices

Three dimensional printing (3DP), or additive manufacturing, is an exponentially growing process in the fabrication of various technologies with applications in sectors such as electronics, biomedical, pharmaceutical and tissue engineering. Micro and nano scale printing is encouraging the innovation of the aforementioned sectors, due to the ability to control design, material and chemical properties at a highly precise level, which is advantageous in creating a high surface area to volume ratio and altering the overall products’ mechanical and physical properties. In this review, micro/-nano printing technology, mainly related to lithography, inkjet and electrohydrodynamic (EHD) printing and their biomedical and electronic applications will be discussed. The current limitations to micro/-nano printing methods will be examined, covering the difficulty in achieving controlled structures at the miniscule micro and nano scale required for specific applications