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        <title>Frontiers in Electronics | Wearable Electronics section | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/electronics/sections/wearable-electronics</link>
        <description>RSS Feed for Wearable Electronics section in the Frontiers in Electronics journal | New and Recent Articles</description>
        <language>en-us</language>
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        <pubDate>2026-04-04T06:21:54.487+00:00</pubDate>
        <ttl>60</ttl>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/felec.2025.1704891</guid>
        <link>https://www.frontiersin.org/articles/10.3389/felec.2025.1704891</link>
        <title><![CDATA[Efficient communication channel for smart contact lens with resonant magnetoquasistatic coupling]]></title>
        <pubdate>2026-02-11T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Sukriti Shaw</author><author>Mayukh Nath</author><author>Arunashish Datta</author><author>Shreyas Sen</author>
        <description><![CDATA[Magnetic resonant coupling is widely used for wireless power transfer in wearables but is typically employed in the strongly coupled regime, where the separation is smaller than or comparable to the device size. This work instead exploits resonant magnetoquasistatic (MQS) coupling to realize a wireless communication link between a necklace-mounted transmitter (Tx) coil and a receiver (Rx) coil embedded in a smart contact lens (SCL). A 15-cm Tx coil and an 8-mm peripheral Rx coil, operating at approximately 26.8 MHz at axial separations of ≈15 cm and lateral offsets ≥9 cm, form a weakly coupled but robust near-field channel. Finite-element simulations show only ∼10 dB path-loss variation across misalignments and a ∼5 Mbps channel capacity over 1 MHz bandwidth, sufficient for compressed 480p/15 fps video and multi-sensor telemetry. Because ocular and facial tissues have μr≈1 below 30 MHz, their presence causes negligible additional attenuation. A benchtop prototype with a 20-cm single-turn Tx coil and 1-cm four-turn Rx coil tuned near 26 MHz shows ∼60 dB of channel loss over necklace–eye distances and weak sensitivity to a tissue phantom, supporting the MQS-based analysis. Together, these results establish resonant MQS coupling as a viable high-data-rate communication backbone for future smart contact lenses.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/felec.2025.1668332</guid>
        <link>https://www.frontiersin.org/articles/10.3389/felec.2025.1668332</link>
        <title><![CDATA[Effective connectivity-based recognition of mental fatigue patterns using functional near-infrared spectroscopy]]></title>
        <pubdate>2025-10-15T00:00:00Z</pubdate>
        <category>Brief Research Report</category>
        <author>Neda Abdollahpour</author><author>N. Sertac Artan</author>
        <description><![CDATA[Mental Fatigue (MF) impairs cognitive performance and alters brain function, yet its underlying neurophysiological mechanisms remain insufficiently understood. While prior functional Near-Infrared Spectroscopy (fNIRS) studies have focused primarily on signal-level changes or undirected connectivity, few have explored how MF modulates causal interactions within cortical networks. In this study, we employed an Effective Connectivity (EC) framework based on generalized partial directed coherence (GPDC) to investigate directional brain dynamics during a cognitively demanding Stroop task. Using a publicly available dataset comprising continuous fNIRS recordings from 21 healthy adults, we modeled EC across six temporal segments to capture the evolving structure of brain networks. Our results revealed a transition from distributed, flexible connectivity patterns to more rigid and stereotyped configurations, particularly within prefrontal and motor regions. These findings were supported by significant changes in EC intensity in key channels over time. Together, our approach highlights the utility of directional connectivity analysis for identifying neural signatures of MF and contributes toward developing more sensitive biomarkers for real-time fatigue monitoring.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/felec.2025.1566899</guid>
        <link>https://www.frontiersin.org/articles/10.3389/felec.2025.1566899</link>
        <title><![CDATA[Quantitative musculoskeletal monitoring and analysis in aquatic rehabilitation]]></title>
        <pubdate>2025-04-02T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Abu Bony Amin</author><author>Ebenezer Asabre</author><author>Sina Razaghi</author><author>Yeonsik Noh</author>
        <description><![CDATA[The benefits of aquatic rehabilitation have been demonstrated to promote wellbeing and facilitate motor recovery in middle-aged adults and geriatrics. Individualized patient-centered treatment is essential to accelerate and improve the rehabilitation process of neurological and orthopedic patients. Although aquatic therapy and rehabilitation are well known to be beneficial to these populations, it can be challenging for therapists to visualize and monitor patient progress and provide individualized feedback to ensure correct movement as planned. To establish the suitability of the developed wearable device in an aquatic environment, this study compared the extracted features of the sEMG and IMU data in on-land and aquatic environments for the bicep curls (BC) and tricep kickback (TK) protocols. We conducted a systematic analysis of the reproducibility and precision of the sEMG-IMU characteristics to assess the feasibility of the device for practical applications. While time and frequency domain features of sEMG were higher in aquatic environments compared to on-land, the Intraclass Correlation Coefficient (ICC) for these features ranged from 0.81 to 0.98, and the Coefficient of Variation (CV%) exhibited a range of 5.7% to 14.4%, highlighting reproducibility and correlation across environments in the two protocols. Environment. Moreover, for frequency domain the reproducibility and precision of the sEMG recordings for each muscle in this study were obtained high (ICC=0.92−0.96, CV%=5.4−13.8%). It’s noticeable that the observed acceleration data is almost similar to the same movement was maintained throughout the exercise. Eventually, the quantitative result is used to cluster the protocol types along with various repetitions to promote the personalized aquatic rehabilitation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/felec.2025.1501178</guid>
        <link>https://www.frontiersin.org/articles/10.3389/felec.2025.1501178</link>
        <title><![CDATA[Low-loss power management strategy for weak and low-frequency biomechanical energy harvesting for new generation wearable electronics]]></title>
        <pubdate>2025-02-14T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Weilu Li</author><author>Yongcan Huang</author><author>Chunhua Liu</author><author>Agnes Valencia</author><author>Walid A. Daoud</author>
        <description><![CDATA[IntroductionAmidst the rapidly growing development of wearable electronics, their dependence on external power sources increases the power expense while leading to interruptions of their operation during charging. Biomechanical energy harvesters offer a promising solution for self-powered wearable electronics by converting waste kinetic energy to electricity. Despite successful efforts in advancing their power outputs from μW to mW, several challenges persist, including low output current at the μA-level, high internal impedance in the GΩ-level, and AC outputs, restricting their practical applications. Conventional power management circuits are commonly utilized in high-frequency harvesters without adequate consideration of the energy loss that incurs, potentially leading to circuit failure when used in low-frequency harvesters with a lower power output.MethodsHere, we introduce a low-loss power management circuit (L-PMC) that functions under low-frequency conditions to facilitate biomechanical energy harvesting.ResultsOur innovative two-stage energy transfer strategy boosts the energy extraction efficiency to 42.24%, breaking previous records. With an energy transfer efficiency of 30.59%, L-PMC can charge a battery from 1.9 V to 2.4 V in just 10 min.DiscussionMoreover, the integration of passive current amplification tripled charge accumulation and energy storage, representing 207% enhancement in energy transfer efficiency, presenting a versatile and universal approach to low-frequency biomechanical energy harvesting for new generation wearable electronics.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/felec.2024.1503424</guid>
        <link>https://www.frontiersin.org/articles/10.3389/felec.2024.1503424</link>
        <title><![CDATA[Comparative analysis of force sensitive resistor circuitry for use in force myography systems for hand gesture recognition]]></title>
        <pubdate>2024-12-10T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Giancarlo K. Sagastume</author><author>Peyton R. Young</author><author>Marcus A. Battraw</author><author>Justin G. Kwong</author><author>Jonathon S. Schofield</author>
        <description><![CDATA[Wearable technologies for hand gesture classification are becoming increasingly prominent due to the growing need for more natural, human-centered control of complex devices. This need is particularly evident in emerging fields such as virtual reality and bionic prostheses, which require precise control with minimal delay. One method used for hand gesture recognition is force myography (FMG), which utilizes non-invasive pressure sensors to measure radial muscle forces on the skin’s surface of the forearm during hand movements. These sensors, typically force-sensitive resistors (FSRs), require additional circuitry to generate analog output signals, which are then classified using machine learning to derive corresponding control signals for the device. The performance of hand gesture classification can be influenced by the characteristics of this output signal, which may vary depending on the circuitry used. Our study examined three commonly used circuits in FMG systems: the voltage divider (VD), unity gain amplifier (UGA), and transimpedance amplifier (TIA). We first conducted benchtop testing of FSRs to characterize the impact of this circuitry on linearity, deadband, hysteresis, and drift, all metrics with the potential to influence an FMG system’s performance. To evaluate the circuit’s performance in hand gesture classification, we constructed an FMG band with 8 FSRs, using an adjustable Velcro strap and interchangeable circuitry. Wearing the FMG band, participants (N = 15) were instructed to perform 10 hand gestures commonly used in daily living. Our findings indicated that the UGA circuit outperformed others in minimizing hysteresis, drift and deadband with comparable results to the VD, while the TIA circuit excelled in ensuring linearity. Further, contemporary machine learning algorithms used to detect hand gestures were unaffected by the circuitry employed. These results suggest that applications of FMG requiring precise sensing of force values would likely benefit from use of the UGA. Alternatively, if hand gesture state classification is the only use case, developers can take advantage of benefits offered from using less complex circuitry such as the VD.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/felec.2024.1238967</guid>
        <link>https://www.frontiersin.org/articles/10.3389/felec.2024.1238967</link>
        <title><![CDATA[Impact of head-down-tilt body position on abdomen resistance for urinary bladder monitory applications]]></title>
        <pubdate>2024-03-08T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Todd J. Freeborn</author><author>Shelby Critcher</author><author>Gwendolyn L. Hooper</author>
        <description><![CDATA[Tissue electrical impedance (or bioimpedance) is a quantity related to the passive, frequency-dependent electrical properties of a biological tissue and is a promising modality for continuous monitoring of relative bladder volume and bladder activity. In this study, the impact of body position [specifically 6° head-down tilt (HDT)] intended to induce fluid redistribution and, therefore, result in a change in the electrical resistance of the abdomen is evaluated. The abdomen resistance (10 kHz–100 kHz) of nine healthy young adults was measured before and after 240 min in a 6° HDT position. Over this period, the resistance increase was not statistically significant even though the average bladder volume increased by 506 mL. It was expected that the abdomen resistance would decrease with an increase in bladder volume over this period. The masking of the expected resistance decrease is attributed to the shift in the fluid from the legs/abdomen to the neck/chest caused by the HDT body position over this period. Overall, this suggests that methods to differentiate bladder volume changes from other types of fluid shifts in the body are needed for resistance-based monitoring under free-living conditions.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/felec.2023.1315132</guid>
        <link>https://www.frontiersin.org/articles/10.3389/felec.2023.1315132</link>
        <title><![CDATA[A new e-health cloud-based system for cardiovascular risk assessment]]></title>
        <pubdate>2023-12-22T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>G. Tatsis</author><author>G. Baldoumas</author><author>V. Christofilakis</author><author>P. Kostarakis</author><author>P. A. Varotsos</author><author>N. V. Sarlis</author><author>E. S. Skordas</author><author>A. Bechlioulis</author><author>L. K. Michalis</author><author>K. K. Naka</author>
        <description><![CDATA[Sudden cardiac death (SCD) is one of the leading causes of death worldwide. Many individuals have no cardiovascular symptoms before the SCD event. As a result, the ability to identify the risk before such an event is extremely limited. Timely and accurate prediction of SCD using new electronic technologies is greatly needed. In this work, a new innovative e-health cloud-based system is presented that allows a stratification of SCD risk based on the method of natural time entropy variability analysis. This innovative, non-invasive system can be used easily in any setting. The e-health cloud-based system was evaluated using data from a total of 203 individuals, patients with chronic heart failure (CHF) who are at high risk of SCD and age-matched healthy controls. Statistical analysis was performed in two-time windows of different duration; the first-time window had a duration of 20 min, while the second was 10 min. Employing modern methods of machine learning, classifiers for the discrimination of CHF patients from the healthy controls were obtained for the first as well as the second (half-time) window. The results indicated a very good separation between the two groups, even from samples taken in a 10-min time window. Larger studies are needed to further validate this novel e-health cloud-based system before its use in everyday clinical practice.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/felec.2023.1173607</guid>
        <link>https://www.frontiersin.org/articles/10.3389/felec.2023.1173607</link>
        <title><![CDATA[Ear canal pressure sensor for food intake detection]]></title>
        <pubdate>2023-07-18T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Delwar Hossain</author><author>Tonmoy Ghosh</author><author>Masudul Haider Imtiaz</author><author>Edward Sazonov</author>
        <description><![CDATA[Introduction: This paper presents a novel Ear Canal Pressure Sensor (ECPS) for objective detection of food intake, chew counting, and food image capture in both controlled and free-living conditions. The contribution of this study is threefold: 1) Development and validation of a novel wearable sensor that uses changes in ear canal pressure and the device’s acceleration as an indicator of food intake, 2) A method to identify chewing segments and count the number of chews in each eating episode, and 3) Facilitation of egocentric image capture only during eating by triggering camera from sensor detection thus reducing power consumption, privacy concerns, as well as storage and computational cost.Methods: To validate the device, data were collected from 10 volunteers in a controlled environment and three volunteers in a free-living environment. During the controlled activities, each participant wore the device for approximately 1 h, and during the free living for approximately 12 h. The food intake of the participants was not restricted in any way in both part of the experiment. Subject-independent Support Vector Machine classifiers were trained to identify periods of food intake from the features of both the pressure sensor and accelerometer, and features only from the pressure sensor.Results: Results from leave-one-out cross-validation showed an average 5 sec-epoch classification F-score of 87.6% using only pressure sensor features and 88.6% using features from both pressure sensor and accelerometer in the controlled environment. For the free-living environment, both classifiers accurately detected all eating episodes. The wearable sensor achieves 95.5% accuracy in counting the number of chews with respect to manual annotation from the videos of the eating episodes using a pressure sensor classifier in the controlled environment.Discussion: The manual review of the images found that only 3.7% of captured images belonged to the detected eating episodes, suggesting that sensor-triggered camera capture may facilitate reducing the number of captured images and power consumption of the sensor.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/felec.2022.1060197</guid>
        <link>https://www.frontiersin.org/articles/10.3389/felec.2022.1060197</link>
        <title><![CDATA[Analytic circuit model for thermal drying behavior of electronic inks]]></title>
        <pubdate>2023-01-06T00:00:00Z</pubdate>
        <category>Brief Research Report</category>
        <author>Gabriel Maroli</author><author>Santiago Boyeras</author><author>Hernan Giannetta</author><author>Sebastian Pazos</author><author>Joel Gak</author><author>Alejandro Raúl Oliva</author><author>María Alicia Volpe</author><author>Pedro Marcelo Julian</author><author>Felix Palumbo</author>
        <description><![CDATA[Understanding the sintering process of conductive inks is a fundamental step in the development of sensors. The intrinsic properties (such as thermal conductivity, resistivity, thermal coefficient, among others) of the printed devices do not correspond to those of the bulk materials. In the field of biosensors porosity plays a predominant role, since it defines the difference between the geometric area of the working electrode and its electrochemical surface area. The analysis reported so far in the literature on the sintering of inks are based on their DC characterization. In this work, the shape and distribution of the nanoparticles that make up the silver ink have been studied employing a transmission electron microscopy. Images of the printed traces have been obtained through a scanning electron microscope at different sintering times, allowing to observe how the material decreases its porosity over time. These structural changes were supported through electrical measurements of the change in the trace impedance as a function of drying time. The resistivity and thermal coefficient of the printed tracks were analyzed and compared with the values of bulk silver. Finally, this work proposes an analytical circuit model of the drying behavior of the ink based on AC characterization at different frequencies. The characterization considers an initial time when the spheric nanoparticles are still surrounded by the capping agent until the conductive trace is obtained. This model can estimate the characteristics that the printed devices would have, whether they are used as biosensors (porous material) or as interconnections (compact material) in printed electronics.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/felec.2022.1071132</guid>
        <link>https://www.frontiersin.org/articles/10.3389/felec.2022.1071132</link>
        <title><![CDATA[A review and analysis of current-mode biosensing front-end ICs for nanopore-based DNA sequencing]]></title>
        <pubdate>2022-11-29T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Xu Liu</author><author>Qiumeng Fan</author><author>Zhijie Chen</author><author>Peiyuan Wan</author><author>Wei Mao</author><author>Hao Yu</author>
        <description><![CDATA[Bio-sensors connect the biological world with electronic devices, widely used in biomedical applications. The combination of microelectronic and medical technologies makes biomedical diagnosis more rapid, accurate, and efficient. In this article, the current-mode biosensing front-end integrated circuits (ICs) for nanopore-based DNA sequencing are reviewed and analyzed, aiming to present their operation theories, advantages, limitations, and performances including gain, bandwidth, noise, and power consumption. Because biological information and external interference are contained in extremely weak sensing current, usually at the pA or nA level, it is challenging to accurately detect and restore the desired signals. Based on the requirements of DNA sequencing, this paper shows three circuit topologies of biosensing front-end, namely, discrete-time, continuous-time, and current-to-frequency conversion types. This paper also makes an introduction to the current-mode sensor array for DNA sequencing. To better review and evaluate the research of the state-of-the-art, the most relevant published works are summarized and compared. The review and analysis would help the researchers be familiar with the requirements, constraints, and methods for current-mode biosensing front-end IC designs for nanopore-based DNA sequencing.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/felec.2022.1017511</guid>
        <link>https://www.frontiersin.org/articles/10.3389/felec.2022.1017511</link>
        <title><![CDATA[Kinetic energy harvesting based sensing and IoT systems: A review]]></title>
        <pubdate>2022-10-06T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Zijie Chen</author><author>Fei Gao</author><author>Junrui Liang</author>
        <description><![CDATA[The rapid advance of the Internet of Things (IoT) has attracted growing interest in academia and industry toward pervasive sensing and everlasting IoT. As the IoT nodes exponentially increase, replacing and recharging their batteries proves an incredible waste of labor and resources. Kinetic energy harvesting (KEH), converting the wasted ambient kinetic energy into usable electrical energy, is an emerging research field where various working mechanisms and designs have been developed for improved performance. Leveraging the KEH technologies, many motion-powered sensors, where changes in the external environment are directly converted into corresponding self-generated electrical signals, are developed and prove promising for multiple self-sensing applications. Furthermore, some recent studies focus on utilizing the generated energy to power a whole IoT sensing system. These systems comprehensively consider the mechanical, electrical, and cyber parts, which lead a further step to truly self-sustaining and maintenance-free IoT systems. Here, this review starts with a brief introduction of KEH from the ambient environment and human motion. Furthermore, the cutting-edge KEH-based sensors are reviewed in detail. Subsequently, divided into two aspects, KEH-based battery-free sensing systems toward IoT are highlighted. Moreover, there are remarks in every chapter for summarizing. The concept of self-powered sensing is clarified, and advanced studies of KEH-based sensing in different fields are introduced. It is expected that this review can provide valuable references for future pervasive sensing and ubiquitous IoT.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/felec.2022.906324</guid>
        <link>https://www.frontiersin.org/articles/10.3389/felec.2022.906324</link>
        <title><![CDATA[Reliability of pulse photoplethysmography sensors: Coverage using different setups and body locations]]></title>
        <pubdate>2022-09-29T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Pablo Armañac-Julián</author><author>Spyridon Kontaxis</author><author>Andrius Rapalis</author><author>Vaidotas Marozas</author><author>Pablo Laguna</author><author>Raquel Bailón</author><author>Eduardo Gil</author><author>Jesús Lázaro</author>
        <description><![CDATA[Pulse photoplethysmography (PPG) is a simple and economical technique for obtaining cardiovascular information. In fact, PPG has become a very popular technology among wearable devices. However, the PPG signal is well-known to be very vulnerable to artifacts, and a good quality signal cannot be expected for most of the time in daily life. The percentage of time that a given measurement can be estimated (e.g., pulse rate) is denoted coverage (C), and it is highly dependent on the subject activity and on the configuration of the sensor, location, and stability of contact. This work aims to quantify the coverage of PPG sensors, using the simultaneously recorded electrocardiogram as a reference, with the PPG recorded at different places in the body and under different stress conditions. While many previous works analyzed the feasibility of PPG as a surrogate for heart rate variability analysis, there exists no previous work studying coverage to derive other cardiovascular indices. We report the coverage not only for estimating pulse rate (PR) but also for estimating pulse arrival time (PAT) and pulse amplitude variability (PAV). Three different datasets are analyzed for this purpose, consisting of a tilt-table test, an acute emotional stress test, and a heat stress test. The datasets include 19, 120, and 51 subjects, respectively, with PPG at the finger and at the forehead for the first two datasets and at the earlobe, in addition, for the latter. C ranges from 70% to 90% for estimating PR. Regarding the estimation of PAT, C ranges from 50% to 90%, and this is very dependent on the PPG sensor location, PPG quality, and the fiducial point (FP) chosen for the delineation of PPG. In fact, the delineation of the FP is critical in time for estimating derived series such as PAT due to the small dynamic range of these series. For the estimation of PAV, the C rates are between 70% and 90%. In general, lower C rates have been obtained for the PPG at the forehead. No difference in C has been observed between using PPG at the finger or at the earlobe. Then, the benefits of using either will depend on the application. However, different C rates are obtained using the same PPG signal, depending on the FP chosen for delineation. Lower C is reported when using the apex point of the PPG instead of the maximum flow velocity or the basal point, with a difference from 1% to even 10%. For further studies, each setup should first be analyzed and validated, taking the results and guidelines presented in this work into account, to study the feasibility of its recording devices with respect to each specific application.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/felec.2022.906689</guid>
        <link>https://www.frontiersin.org/articles/10.3389/felec.2022.906689</link>
        <title><![CDATA[Detection of Atrial Fibrillation in Compressively Sensed Electrocardiogram for Remote Monitoring]]></title>
        <pubdate>2022-07-01T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Mohamed Abdelazez</author><author>Sreeraman Rajan</author><author>Adrian D. C. Chan</author>
        <description><![CDATA[The objective of this paper is to develop an optimized system to detect Atrial Fibrillation (AF) in compressively sensed electrocardiogram (ECG) for long-term remote patient monitoring. A three-stage system was developed to 1) reject ECG of poor signal quality, 2) detect AF in compressively sensed ECG, and 3) detect AF in selectively reconstructed ECG. The Long-Term AF Database (LTAFDB), sampled at 128 Hz using a 12-bit ADC with a range of 20 mV, was used to validate the system. The LTAFDB had 83,315 normal and 82,435 AF rhythm 30 s ECG segments. Clean ECG from the LTAFDB was artificially contaminated with motion artifact to achieve −12 to 12 dB Signal-to-Noise Ratio (SNR) in steps of 3 dB. The contaminated ECG was compressively sensed at 50% and 75% compression ratio (CR). The system was evaluated using average precision (AP), the area under the curve (AUC) of the receiver operator characteristic curve, and the F1 score. The system was optimized to maximize the AP and minimize ECG rejection and reconstruction ratios. The optimized system for 50% CR had 0.72 AP, 0.63 AUC, and 0.58 F1 score, 0.38 rejection ratio, and 0.38 reconstruction ratio. The optimized system for 75% CR had 0.72 AP, 0.63 AUC, and 0.59 F1 score, 0.40 rejection ratio, and 0.35 reconstruction ratio. Challenges for long-term AF monitoring are the short battery life of monitors and the high false alarm rate due to artifacts. The proposed system improves the short battery life through compressive sensing while reducing false alarms (high AP) and ECG reconstruction (low reconstruction ratio).]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/felec.2022.910968</guid>
        <link>https://www.frontiersin.org/articles/10.3389/felec.2022.910968</link>
        <title><![CDATA[A Procedural Method to Predictively Assess Power-Quality Trade-Offs of Circuit-Level Adaptivity in IoT Systems]]></title>
        <pubdate>2022-06-27T00:00:00Z</pubdate>
        <category>Hypothesis and Theory</category>
        <author>Jaro De Roose</author><author>Martin Andraud</author><author>Marian Verhelst</author>
        <description><![CDATA[The constant miniaturization of IoT sensor nodes requires a continuous reduction in battery sizes, leading to more stringent needs in terms of low-power operation. Over the past decades, an extremely large variety of techniques have been introduced to enable such reductions in power consumption. Many involve some form of offline reconfigurability (OfC), i.e., the ability to configure the node before deployment, or online adaptivity (OnA), i.e., the ability to also reconfigure the node during run time. Yet, the inherent design trade-offs usually lead to ad hoc OnA and OfC, which prevent assessing the varying benefits and costs each approach implies before investing in implementation on a specific node. To solve this issue, in this work, we propose a generic predictive assessment methodology that enables us to evaluate OfC and OnA globally, prior to any design. Practically, the methodology is based on optimization mathematics, to quickly and efficiently evaluate the potential benefits and costs from OnA relative to OfC. This generic methodology can, thus, determine which type of solution will consume the least amount of power, given a specific application scenario, before implementation. We applied the methodology to three adaptive IoT system studies, to demonstrate the ability of the introduced methodology, bring insights into the adaptivity mechanics, and quickly optimize the OfC–OnA adaptivity, even under scenarios with many adaptivity variables.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/felec.2022.935289</guid>
        <link>https://www.frontiersin.org/articles/10.3389/felec.2022.935289</link>
        <title><![CDATA[Editorial: Wearable and Implantable Electronics for the next Generation of Human-Machine Interactive Devices]]></title>
        <pubdate>2022-06-15T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Yu Wu</author><author>Shiwei Wang</author><author>Boyang Shen</author><author>Hubin Zhao</author><author>Haichang Lu</author><author>Shuo Gao</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/felec.2022.866527</guid>
        <link>https://www.frontiersin.org/articles/10.3389/felec.2022.866527</link>
        <title><![CDATA[Fabrication of a Flexible Aqueous Textile Zinc-Ion Battery in a Single Fabric Layer]]></title>
        <pubdate>2022-06-06T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Sheng Yong</author><author>Nicholas Hillier</author><author>Stephen Beeby</author>
        <description><![CDATA[Zinc-ion batteries (ZIB), with various manganese oxide-based cathodes, provide a promising solution for textile-based flexible energy storage devices. This paper demonstrates, for the first time, a flexible aqueous ZIB with manganese-based cathode fabricated in a single woven polyester cotton textile. The textile was functionalized with a flexible polymer membrane layer that fills the gaps between textile yarns, enabling fine control over the depth of penetration of the spray deposited manganese oxide cathode and zinc anode. This leaves an uncoated region in the textile-polymer network that acts as the battery’s separator. The textile battery cell was vacuum impregnated with the aqueous electrolyte, achieving good wettability of the electrodes with the electrolyte. Additionally, the choice of cathodic material and its influence over the electrochemical performance of the zinc ion battery was investigated with commercially available Manganese (IV) oxide and Manganese (II, III) oxide. The textile ZIB with Manganese (II, III) oxide cathode (10.9 mAh g−1 or 35.6 µA h.cm−2) achieved better performance than the textile ZIB with Manganese (IV) oxide (8.95 mAh g−1 or 24.2 µAh cm−2) at 1 mA cm−2 (0.3 A g−1). This work presents a novel all-textile battery architecture and demonstrates the capability of using manganese oxides as cathodes for a full textile-based flexible aqueous ZIB.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/felec.2022.895001</guid>
        <link>https://www.frontiersin.org/articles/10.3389/felec.2022.895001</link>
        <title><![CDATA[Towards Next Generation Cleaning Tools: Factors Affecting Cleaning Robot Usage and Proxemic Behaviors Design]]></title>
        <pubdate>2022-04-29T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yuhao Chen</author><author>Yue Luo</author><author>Boyi Hu</author>
        <description><![CDATA[Among all healthcare sectors and working processes, the janitorial section is a prominent source of work-related injuries due to its labor-intensive nature and rising need for a hygienic environment, thus requiring extra attention for prevention strategies. Advancement in robotic technology has allowed autonomous cleaning robots to be a viable solution to ease the burden of janitors. To evaluate the application of commercial-grade cleaning robots, a video-based survey was developed and distributed to participants. Results from 117 participants revealed that: 1) participants were less tolerant when their personal space was invaded by humans compared with the cleaning robot, 2) it is better to inform the surrounding humans that the cleaning robot has been sanitized to make them feel safe and comfortable during the pandemic, and 3) to make the interaction more socially acceptable, the cleaning robot should respect human personal space, especially when there is ample space to maneuver. The findings of the present study provide insight into the usage and Proxemic behaviors design of future cleaning robots.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/felec.2022.824981</guid>
        <link>https://www.frontiersin.org/articles/10.3389/felec.2022.824981</link>
        <title><![CDATA[System Performance and User Feedback Regarding Wearable Bioimpedance System for Multi-Site Knee Tissue Monitoring: Free-Living Pilot Study With Healthy Adults]]></title>
        <pubdate>2022-04-21T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Shelby Critcher</author><author>Todd J. Freeborn</author>
        <description><![CDATA[Knee-focused wearable devices have the potential to support personalized rehabilitation therapies by monitoring localized tissue alterations related to activities that reduce functional symptoms and pain. However, supporting these applications requires reported data to be reliable and accurate which can be challenging in the unsupervised free-living conditions that wearable devices are deployed. This pilot study has assessed a knee-focused wearable sensor system to quantify 1) system performance (operation, rates of data artifacts, environment impacts) to estimate realistic targets for reliable data with this system and 2) user experiences (comfort, fit, usability) to help inform future designs to increase usability and adoption of knee-focused wearables. Study data was collected from five healthy adult participants over 2 days, with 84.5 and 35.9% of artifact free data for longitudinal and transverse electrode configurations. Small to moderate positive correlations were also identified between changes in resistance, temperature, and humidity with respect to acceleration to highlight how this system can be used to explore relationships between knee tissues and environmental/activity context.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/felec.2021.790081</guid>
        <link>https://www.frontiersin.org/articles/10.3389/felec.2021.790081</link>
        <title><![CDATA[Wearable System to Guide Crosswalk Navigation for People With Visual Impairment]]></title>
        <pubdate>2022-03-03T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Hojun Son</author><author>James Weiland</author>
        <description><![CDATA[Independent travelling is a significant challenge for visually impaired people in urban settings. Traditional and widely used aids such as guide dogs and long canes provide basic guidance and obstacle avoidance but are not sufficient for complex situations such as street crossing. We propose a new wearable system that can safely guide a user with visual impairment at a signalized crosswalk. Safe street crossing is an important element of fully independent travelling for people who are blind or visually impaired (BVI), but street crossing is challenging for BVI because it involves several steps reliant on vision, including scene understanding, localization, object detection, path planning, and path following. Street crossing also requires timely completion. Prior solutions for guiding BVI in crosswalks have focused on either detection of crosswalks or classifying crosswalks signs. In this paper, we demonstrate a system that performs all the functions necessary to safely guide BVI at a signalized crosswalk. Our system utilizes prior maps, similar to how autonomous vehicles are guided. The hardware components are lightweight such that they can be wearable and mobile, and all are commercially available. The system operates in real-time. Computer vision algorithms (Orbslam2) localize the user in the map and orient them to the crosswalk. The state of the crosswalk signal (don’t walk or walk) is detected (using a convolutional neural network), the user is notified (via verbal instructions) when it is safe to cross, and the user is guided (via verbal instructions) along a path towards a destination on the prior map. The system continually updates user position relative to the path and corrects the user’s trajectory with simple verbal commands. We demonstrate the system functionality in three BVI participants. With brief training, all three were able to use the system to successfully navigate a crosswalk in a safe manner.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/felec.2021.807051</guid>
        <link>https://www.frontiersin.org/articles/10.3389/felec.2021.807051</link>
        <title><![CDATA[Physically Secure Wearable–Wearable Through-Body Interhuman Body Communication]]></title>
        <pubdate>2022-02-03T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>David Yang</author><author>Shovan Maity</author><author>Shreyas Sen</author>
        <description><![CDATA[Human body communication (HBC) has recently emerged as an alternative method to connect devices on and around the human body utilizing the electrical conductivity properties of the human body. HBC can be utilized to enable new interaction modalities between computing devices by enhancing the natural interaction of touch. It also provides the inherent benefit of security and energy-efficiency compared to a traditional wireless communication, such as Bluetooth, making it an attractive alternative. However, most state-of-the-art HBC demonstrations show communication between a wearable and an Earth ground–connected device, and there have been very few implementations of HBC systems demonstrating communication between two wearable devices. Also, most of the HBC implementations suffer from the problem of signal leakage out of the body which enables communication even without direct contact with the body. In this article, we present BodyWire which uses an electro-quasistatic HBC (EQS-HBC) technique to enable communication between two wearable devices and also confine the signal to a very close proximity to the body. We characterize the human body channel loss under different environment (office desk, laboratory, and outdoors), posture, and body location conditions to ascertain the effect of each of these on the overall channel loss. The measurement results show that the channel loss varies within a range of 15dB across all different posture, environmental conditions, and body location variation, illustrating the dynamic range of the signal available at the input of any receiver. Leakage measurements are also carried out from the devices to show the distance over which the signal is available away from the body to illustrate the security aspect of HBC and show its effect on the channel loss measurements. For the first time, a through-body interhuman channel loss characterization is presented. Finally, a demonstration of secure interhuman information exchange between two battery-operated wearable devices is shown through the BodyWire prototype, which shows the smallest form factor HBC demonstration according to the authors’ best knowledge.]]></description>
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