Wearable Biomedical Devices Research Articles

Fabrication and Characterization of a Flexible Ag/AgCl-Zn Battery for Biomedical Applications

A flexible silver-zinc fabric-based primary battery that is biocompatible, conformable, and suitable for single-use wearable biomedical devices is reported. The planar battery was fabricated by screen printing silver/silver-chloride and zinc electrodes (14 mm × 8 mm) onto a silk substrate. A biologically relevant fluid, phosphate buffered saline was used as a liquid electrolyte for characterization. Cyclic voltammetry, electrochemical impedance spectroscopy, and current discharge properties at constant densities of 0.89 μA/cm2, 8.93 μA/cm2, and 89.29 μA/cm2 were used to quantify battery performance. Nine cells were placed in series to generate a greater open circuit voltage (>6 V) relevant to previously reported biomedical applications. The nine-cell battery was evaluated for operation under mechanical strain due to likely placement on curved surfaces of the body in wearable applications. The nine-cell battery was discharged over 4 h at 8.93 μA/cm2 in an unstrained condition. The mechanically strained battery when mounted to a mannequin to mimic anatomical curvature discharged up to 30 min faster. Additionally, the nine-cell battery was used in an in vitro wound model to power an electroceutical, showing promise towards practical use in active, corrosive, and potentially biohazardous environments.

Giant reduction of thermal conductivity and enhancement of thermoelectric performance in twinning superlattice InAsSb nanowires

Semiconductor nanostructures hold great promise for high-efficiency waste-heat recovery exploiting thermoelectric energy conversion. They could significantly contribute to the implementation of environmentally friendly energy sources and to the realization of self-powered biomedical wearable devices. A crucial thermoelectric material requirement is a reduced thermal conductivity together with good electrical transport properties. In this work we demonstrate a drastic reduction of the thermal conductivity in III-V semiconductor nanowires as a result of the introduction of periodic crystal-lattice twin planes during growth. The electrical and thermal transport of these nanostructures, known as twinning superlattice nanowires, are probed and compared with their twin-free counterparts, showing a one order of magnitude decrease of thermal conductivity while maintaining unaltered electrical-transport properties and Seebeck coefficients. This leads to tenfold enhancement of the thermoelectric figure of merit, ZT. Our study reports for the first time the complete experimental measurement of electrical and thermal properties in twinning superlattice nanowires, demonstrating their emergence as a novel class of nanomaterials of great potential for high-efficiency thermoelectric-energy harvesting.

Tiny CNN for Seizure Prediction in Wearable Biomedical Devices.

Epilepsy is a life-threatening disease affecting millions of people all over the world. Artificial intelligence epileptic predictors offer excellent potential to improve epilepsy therapy. Particularly, deep learning models such as convolutional neural networks (CNN) can be used to accurately detect ictogenesis through deep structured learning representations. In this work, a tiny one-dimensional stacked convolutional neural network (1DSCNN) is proposed based on short-time Fourier transform (STFT) to predict epileptic seizure. The results demonstrate that the proposed method obtains better performance compared to recent state-of-the-art methods, achieving an average sensitivity of 94.44%, average false prediction rate (FPR) of 0.011/h and average area under the curve (AUC) of 0.979 on the test set of the American Epilepsy Society Seizure Prediction Challenge dataset, while featuring a model size of only 21.32kB. Furthermore, after adapting the model to 4-bit quantization, its size is significantly decreased by 7.08x with only 0.51% AUC score precision loss, which shows excellent potential for hardware-friendly wearable implementation.

Design of a Low-Power Low-Noise ECG Amplifier for Smart Wearable Devices Using 180nm CMOS Technology

Wearable biomedical devices for recording electrocardiograms (ECG) are becoming more and more popular as they provide clinicians with a comprehensive view of a patient's diagnosis. ECG signals are characterized by low amplitude and are susceptible to many kinds of noise, so high gain and high common mode rejection ratio (CMRR) are essential to suppress them, while ultra-low power low noise (AFE) is used for Analog front-end for ECG signal acquisition, based on a Drive Right Leg (DRL) circuit that combines common-mode feedback with high CMRR and a notch filter band with a cutoff frequency of 50, implemented in CMOS 180 nm technology. According to the simulation results, this front-end circuit can yield a mid-band gain of 50.75 dB at -3dB bandwidth from 100mHz to 100 Hz, a Power Supply Rejection Ratio (PSRR) of 113 dB, and a Common Mode Rejection Ratio (CMRR) of 102 dB, exhibit an input-referred noise (IRN) of 1.47 μVrms from 0.1 Hz to 1kHz，corresponding to a noise efficiency factor (NEF) of 2.74. The AFE consumes 1.08 μW from the 1.8V supply voltage.

A Review on Epidermal Nanogenerators: Recent Progress of the Future Self‐Powered Skins

Epidermal nanogenerators (ENGs), defined as nano‐enabled, thin, soft, and flexible skin‐like devices that can convert mechanical and thermal energy into electricity, are emerging as a promising self‐powered technology for wearable biomedical devices. This review covers the discussion of working mechanisms, design strategy, and major requirements of the state‐of‐the‐art ENGs including piezoelectric, triboelectric, pyroelectric, and hybrid. In addition, their representative applications in human–machine interface (HMI), wound healing, and wearable biomedical sensors are described. In particular, a focus has been on the narration of self‐powered ENG‐based biosensors for detecting physical, biochemical, and physiological signals. Despite the encouraging advances over the past decade, the field of ENGs remains in the early stage of development with limited real‐world adoption. There remain a number of challenges such as insufficient energy and power density for powering wearable devices, poor air permeability, limited washability, and durability under severe conditions. The future opportunity lies at the development of better materials and/or designs to tackle these challenges to generate real‐world impact.

Stretchable, Multi-Layered Stack Antenna for Smart/Wearable Electronic Applications.

The development of microelectronics has been achieved by improving its performance through miniaturization. This was possible through the development of silicon-based semiconductor process technology, but recently, the demand for wearable or flexible devices has increased. These devices are made using various functional elements based on materials that are difficult to utilize with semiconductor devices that contain existing hard silicon-based materials and are bent or flexibly stretched. In this study, wireless antennas suitable for wearable devices were implemented in a stretchable form. It was possible to stably receive a wireless signal, even with a strain of 20% or more, and power light-emitting diodes (LEDs), microheaters, etc. By devising a multi-layered stack antenna without the existing semiconductor process, it was possible to improve the antenna’s reception performance. It is expected that this can be applied in various ways to smart wireless sensors and wearable biomedical devices using the near-field communication (NFC) of smartphones.

Advances in Soft and Dry Electrodes for Wearable Health Monitoring Devices.

Electrophysiology signals are crucial health status indicators as they are related to all human activities. Current demands for mobile healthcare have driven considerable interest in developing skin-mounted electrodes for health monitoring. Silver-Silver chloride-based (Ag-/AgCl) wet electrodes, commonly used in conventional clinical practice, provide excellent signal quality, but cannot monitor long-term signals due to gel evaporation and skin irritation. Therefore, the focus has shifted to developing dry electrodes that can operate without gels and extra adhesives. Compared to conventional wet electrodes, dry ones offer various advantages in terms of ease of use, long-term stability, and biocompatibility. This review outlines a systematic summary of the latest research on high-performance soft and dry electrodes. In addition, we summarize recent developments in soft materials, biocompatible materials, manufacturing methods, strategies to promote physical adhesion, methods for higher breathability, and their applications in wearable biomedical devices. Finally, we discuss the developmental challenges and advantages of various dry electrodes, while suggesting research directions for future studies.

A 65nm/0.448 mW EEG processor with parallel architecture SVM and lifting wavelet transform for high-performance and low-power epilepsy detection

In recent years, low-power and wearable biomedical testing devices have emerged as a key answer to the challenges associated with epilepsy disorders, which are prone to crises and require prolonged monitoring. The feature vector of the electroencephalographic (EEG) signal was extracted using the lifting wavelet transform algorithm, and the hardware of the lifting wavelet transform module was optimized using the canonic signed digit (CSD) coding method. A low-power EEG feature extraction circuit with a power consumption of 0.42 mW was constructed. This article employs the support vector machine (SVM) technique after feature extraction to categorize and identify epilepsy. A parallel SVM processing unit was constructed to accelerate classification and identification, and then a high-speed, low-power EEG epilepsy detection processor was implemented. The processor design was completed using TSMC 65 nm technology. The chip size is 0.98 mm2, operating voltage is 1 V, operating frequency is 1 MHz, epilepsy detection latency is 0.91 s, power consumption is 0.448 mW, and energy efficiency of a single classification is 2.23 μJ/class. The CHB-MIT database test results show that this processor has a sensitivity of 91.86% and a false detection rate of 0.17/h. Compared to other processors, this processor is more suitable for portable/wearable devices.

A High-Sensitivity Wide Input-Power-Range Ultra-Low-Power RF Energy Harvester for IoT Applications

Radio frequency energy harvesting (RFEH) is very attractive for the Internet of things (IoT) and self-powered micro-systems such as wearable biomedical devices and wireless sensor networks. This paper proposes, analyzes, and implements a new RF-DC converter in standard 130 nm CMOS technology. The developed converter is designed and optimized for ultra-low-power IoT and wearable biomedical applications using the 900 MHz ISM band. The proposed 10-stage cross-connected rectifier compensates the transistors threshold voltage by using both dynamic and static bias compensation techniques. An analytical model of the rectifier based on the MOSFET transistor equations is presented, allowing optimization of the rectifier as a function of the number of stages and transistors sizing, improving the sensitivity and the input power range of the converter. The measurement results demonstrate a sensitivity of &#x2212;25.5 dBm for 1 V output across a 5-<inline-formula> <tex-math notation="LaTeX">$\text{M}\Omega $ </tex-math></inline-formula> resistive load and &#x2212;29 dBm for a 100 <inline-formula> <tex-math notation="LaTeX">$\text{M}\Omega $ </tex-math></inline-formula> load, which is better than the best previously reported results. The measured peak end-to-end efficiency of the proposed harvester is 42.4&#x0025; at &#x2212;16 dBm input power, delivering 2.19 V to a 450 <inline-formula> <tex-math notation="LaTeX">$\text{k}\Omega $ </tex-math></inline-formula> load.

Metal-organic framework (MOF) facilitated highly stretchable and fatigue-resistant ionogels for recyclable sensors.

Ionogel-based flexible sensors are widely applied in wearable biomedical devices and soft robots. However, the abandoned ionic sensors are rapidly turning into e-waste. Here, we harness the porosity and the coordination of metal sites of metal-organic frameworks (MOFs) to develop physically crosslinked ionogels, which are composed of polymer chains that coordinate with the MOF metal sites. The covalent crosslinking of the host material transformed into reversible bond interactions that significantly enhance the mechanical properties of the MOF-ionogels. The obtained ionogels can endure an 11 000% stretch and exhibit Young's modulus and toughness of 58 MPa and 25 MJ m-3, respectively. In addition, the fracture energy is as high as 125 kJ m-2, outperforming most reported ionogels. Furthermore, the UiO-66-ionogels are fully recyclable and both the mechanical and electrical properties can be restored. The results of this work provide a new vision for the development of future "green" sensors.

Hierarchically Structured Flexible Electrode on Polyimide for Highly Sensitive and Reliable Biosignal Acquisition

Numerous wearable biomedical devices are developed for the continuous monitoring of personal health or condition. Biosignals acquisition with high sensitivity is important for designing wearable biomedical devices. A sensing electrode between the human body and wearable electronics significantly affects the sensitivity of the sensors. In this study, we fabricated hierarchically structured flexible electrodes on polyimide substrate (HSFE-PI) using micro-casting technique and gold nanoparticles electrodeposition. Polyimides provides robust and outstanding electrical characteristics, and the reliability of HSFE-PI was verified with a cyclic bending test. The integration of hierarchical structures significantly increased the surface area of the electrode by 2.06 times. We applied the HSFE-PI for electromyogram (EMG) and glucose sensing applications and achieved high sensitivity enhancement in both applications. The signal-to-noise ratio (SNR) of measured EMG signals was increased by 2.48 times, and the sensitivity of the glucose detection was increased by 1.42 times compared to the planar counterpart.

Biocompatible All-in-One Adhesive Needle-Free Cup Patch for Enhancing Transdermal Drug Delivery.

Patch-type drug delivery has garnered increased attention as an attractive alternative to the existing drug delivery techniques. Thus far, needle phobia and efficient drug delivery remain huge challenges. To address the issue of needle phobia and enhance drug delivery, we developed a needle-free and self-adhesive microcup patch that can be loaded with an ultrathin salmon DNA (SDNA) drug carrier film. This physically integrated system can facilitate efficient skin penetration of drugs loaded into the microcup patch. The system consists of three main components, namely, a cup that acts as a drug reservoir, an adhesive system that attaches the patch to the skin, and physical stimulants that can be used to increase the efficiency of drug delivery. In addition, an ultrathin SDNA/drug film allows the retention of the drug in the cup and its efficient release by dissolution in the presence of moisture. This latter feature has been validated using gelatin as a skin mimic. The cup design itself has been validated by comparing its deformation and displacement with those of a cylindrical structure. Integration of the self-adhesive microcup patch with both ultrasonic waves and an electric current allows the model drug to penetrate the stratum corneum of the skin barrier and the whole epidermis, thereby enhancing transdermal drug delivery and reducing skin irritation. This system can be used as a wearable biomedical device for efficient transdermal and needle-free drug delivery.

Graphene Flake Self-Assembly Enhancement via Stretchable Platforms and External Mechanical Stimuli.

While the green production and application of 2D functional nanomaterials, such as graphene flakes, in films for stretchable and wearable technologies is a promising platform for advanced technologies, there are still challenges involved in the processing of the deposited material to improve properties such as electrical conductivity. In applications such as wearable biomedical and flexible energy devices, the widely used flexible and stretchable substrate materials are incompatible with high-temperature processing traditionally employed to improve the electrical properties, which necessitates alternative manufacturing approaches and new steps for enhancing the film functionality. We hypothesize that a mechanical stimulus, in the form of substrate straining, may provide such a low-energy approach for modifying deposited film properties through increased flake packing and reorientation. To this end, graphene flakes were exfoliated using an unexplored combination of ethanol and cellulose acetate butyrate for morphological and percolative electrical characterization prior to application on polydimethylsiloxane (PDMS) substrates as a flexible and stretchable electrically conductive platform. The deposited percolative free-standing films on PDMS were characterized via in situ resistance strain monitoring and surface morphology measurements over numerous strain cycles, with parameters extracted describing the dynamic modulation of the film’s electrical properties. A reduction in the film resistance and strain gauge factor was found to correlate with the surface roughness and densification of a sample’s (sub)surface and the applied strain. High surface roughness samples exhibited enhanced reduction in resistance as well as increased sensitivity to strain compared to samples with low surface roughness, corresponding to surface smoothing, which is related to the dynamic settling of graphene flakes on the substrate surface. This procedure of incorporating strain as a mechanical stimulus may find application as a manufacturing tool/step for the routine fabrication of stretchable and wearable devices, as a low energy and compatible approach, for enhancing the properties of such devices for either high sensitivity or low sensitivity of electrical resistance to substrate strain.

Recent advances of flexible sensors for biomedical applications

Ultrathin, soft, flexible and stretchable sensors offer good opportunity to design personal health diagnosis and treatment systems by fabricating wearable biomedical devices for continuous health monitoring and preventive medicine. This paper summarizes the recent advances of flexible sensors for next generation biomedical applications. Materials used for flexible sensors are first briefly introduced. Followed to this part, the latest developments of flexible sensors for biomedical applications are discussed in detail, including flexible sensors for skin-attached devices and implantable devices. Finally, the challenges and future research directions of flexible sensors are also discussed in the development of biomedical devices.

Tunable seesaw-like 3D capacitive sensor for force and acceleration sensing

To address the resource-competing issue between high sensitivity and wide working range for a stand-alone sensor, development of capacitive sensors with an adjustable gap between two electrodes has been of growing interest. While several approaches have been developed to fabricate tunable capacitive sensors, it remains challenging to achieve, simultaneously, a broad range of tunable sensitivity and working range in a single device. In this work, a 3D capacitive sensor with a seesaw-like shape is designed and fabricated by the controlled compressive buckling assembly, which leverages the mechanically tunable configuration to achieve high-precision force sensing (resolution ~5.22 nN) and unprecedented adjustment range (by ~33 times) of sensitivity. The mechanical tests under different loading conditions demonstrate the stability and reliability of capacitive sensors. Incorporation of an asymmetric seesaw-like structure design in the capacitive sensor allows the acceleration measurement with a tunable sensitivity. These results suggest simple and low-cost routes to high-performance, tunable 3D capacitive sensors, with diverse potential applications in wearable electronics and biomedical devices.

Reusable flexible dry electrodes for biomedical wearable devices

This paper reports the fabrication and the characterization of novel reusable Flexible Dry Electrodes (FDEs), which can be employed in wearable devices for medical applications, such as bioelectrical impedance analysis (BIA). Two different FDEs were fabricated exploiting two flexible substrates, i.e. polydimethylsiloxane (PDMS) and polyethylene terephthalate (PET), and the deposition of the conductive layers made by silver paste and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS). Performance tests were conducted by measuring the conductivity at the skin interface and the reliability was assessed after several cycles with different disinfectant solutions and artificial sweat as corrosive agent. FDEs were then used in BIA measurements and compared with the commercial single use silver/silver chloride (Ag/AgCl) gel electrodes. The BIA values measured by the fabricated FDEs were comparable with those obtained by commercial electrodes. The results envision the promising and reliable long-term employment of the proposed FDEs in wearable and portable devices.

A portable, self-contained neuroprosthetic hand with deep learning-based finger control

Objective. Deep learning-based neural decoders have emerged as the prominent approach to enable dexterous and intuitive control of neuroprosthetic hands. Yet few studies have materialized the use of deep learning in clinical settings due to its high computational requirements. Approach. Recent advancements of edge computing devices bring the potential to alleviate this problem. Here we present the implementation of a neuroprosthetic hand with embedded deep learning-based control. The neural decoder is designed based on the recurrent neural network architecture and deployed on the NVIDIA Jetson Nano—a compacted yet powerful edge computing platform for deep learning inference. This enables the implementation of the neuroprosthetic hand as a portable and self-contained unit with real-time control of individual finger movements. Main results. A pilot study with a transradial amputee is conducted to evaluate the proposed system using peripheral nerve signals acquired from implanted intrafascicular microelectrodes. The preliminary experiment results show the system’s capabilities of providing robust, high-accuracy (95%–99%) and low-latency (50–120 ms) control of individual finger movements in various laboratory and real-world environments. Conclusion. This work is a technological demonstration of modern edge computing platforms to enable the effective use of deep learning-based neural decoders for neuroprosthesis control as an autonomous system. Significance. The proposed system helps pioneer the deployment of deep neural networks in clinical applications underlying a new class of wearable biomedical devices with embedded artificial intelligence.Clinical trial registration: DExterous Hand Control Through Fascicular Targeting (DEFT). Identifier: NCT02994160.

A CMOS RF Receiver with Improved Resilience to OFDM-Induced Second-Order Intermodulation Distortion for MedRadio Biomedical Devices and Sensors

A MedRadio RF receiver integrated circuit for implanted and wearable biomedical devices must be resilient to the out-of-band (OOB) orthogonal frequency division modulation (OFDM) blocker. As the OFDM is widely adopted for various broadcasting and communication systems in the ultra-high frequency (UHF) band, the selectivity performance of the MedRadio RF receiver can severely deteriorate by the second-order intermodulation (IM2) distortion induced by the OOB OFDM blocker. An analytical investigation shows how the OFDM-induced IM2 distortion power can be translated to an equivalent two-tone-induced IM2 distortion power. It makes the OFDM-induced IM2 analysis and characterization process for a MedRadio RF receiver much simpler and more straightforward. A MedRadio RF receiver integrated circuit with a significantly improved resilience to the OOB IM2 distortion is designed in 65 nm complementary metal-oxide-semiconductor (CMOS). The designed RF receiver is based on low-IF architecture, comprising a low-noise amplifier, single-to-differential transconductance stage, quadrature passive mixer, trans-impedance amplifier (TIA), image-rejecting complex bandpass filter, and fractional phase-locked loop synthesizer. We describe design techniques for the IM2 calibration through the gate bias tuning at the mixer, and the dc offset calibration that overcomes the conflict with the preceding IM2 calibration through the body bias tuning at the TIA. Measured results show that the OOB carrier-to-interference ratio (CIR) performance is significantly improved by 4–11 dB through the proposed IM2 calibration. The measured maximum tolerable CIR is found to be between −40.2 and −71.2 dBc for the two-tone blocker condition and between −70 and −77 dBc for the single-tone blocker condition. The analytical and experimental results of this work will be essential to improve the selectivity performance of a MedRadio RF receiver against the OOB OFDM-blocker-induced IM2 distortion and, thus, improve the robustness of the biomedical devices in harsh wireless environments in the MedRadio and UHF bands.

A compact QRS detection system based on 0.79 μW analog CMOS energy-of-derivative circuit

We propose a novel QRS detection system consisting of compact and low-power blocks: an analog energy-of-derivative operator, comparator, and a refractory period timer. The goal is to offer a mixed-signal alternative to mainstream algorithmic QRS-detection techniques reducing both the overall power consumption and silicon area in wearable or implantable ECG processing systems. Circuit design, simulations, and tests are performed with the 0.18 μm CMOS process. The system performance is evaluated by identifying QRS complexes in a set of 48 pre-filtered data stream ECG records from the MIT/BIH dataset, with classification sensitivity and precision of 97.81% and 99.71%, respectively, combined to reduced power consumption (0.79 μW) and occupy a small silicon area (0.011 mm2). The main contribution is to demonstrate the feasibility of implementing QRS detection with an ultra-low-power analog energy-of-derivative circuit with performance comparable to state-of-the-art algorithmic approaches. The proposed system can be a competitive option to integrated front-ends of implantable or wearable biomedical devices.

Structural Design Optimization of Micro-Thermoelectric Generator for Wearable Biomedical Devices

Wearable sensors to monitor vital health are becoming increasingly popular both in our daily lives and in medical diagnostics. The human body being a huge source of thermal energy makes it interesting to harvest this energy to power such wearables. Thermoelectric devices are capable of converting the abundantly available body heat into useful electrical energy using the Seebeck effect. However, high thermal resistance between the skin and the device leads to low-temperature gradients (2–10 K), making it difficult to generate useful power by this device. This study focuses on the design optimization of the micro-thermoelectric generator for such low-temperature applications and investigates the role of structural geometries in enhancing the overall power output. Electroplated p-type bismuth antimony telluride (BiSbTe) and n-type copper telluride (CuTe) materials’ properties are used in this study. All the simulations and design optimizations were completed following microfabrication constraints along with realistic temperature gradient scenarios. A series of structural optimizations were performed including the thermoelectric pillar geometries, interconnect contact material layers and fill factor of the overall device. The optimized structural design of the micro-thermoelectric device footprint of 4.5 × 3.5 mm2, with 240 thermoelectric leg pairs, showcased a maximum power output of 0.796 mW and 3.18 mW when subjected to the low-temperature gradient of 5 K and 10 K, respectively. These output power values have high potential to pave the way of realizing future wearable devices.