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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic since early 2020. The coronavirus disease 2019 (COVID-19) has already caused more than three million deaths worldwide and affected people's physical and mental health. COVID-19 patients with mild symptoms are generally required to self-isolate and monitor for symptoms at least for 14 days in the case the disease turns towards severe complications. In this work, we overviewed the impact of COVID-19 on the patients' general health with a focus on their cardiovascular, respiratory and mental health, and investigated several existing patient monitoring systems. We addressed the limitations of these systems and proposed a wearable telehealth solution for monitoring a set of physiological parameters that are critical for COVID-19 patients such as body temperature, heart rate, heart rate variability, blood oxygen saturation, respiratory rate, blood pressure, and cough. This physiological information can be further combined to potentially estimate the lung function using artificial intelligence (AI) and sensor fusion techniques. The prototype, which includes the hardware and a smartphone app, showed promising results with performance comparable to or better than similar commercial devices, thus potentially making the proposed system an ideal wearable solution for long-term monitoring of COVID-19 patients and other chronic diseases.

Maintaining good mobility with ease and freedom of movement is important for an individual’s health and active aging. The knee joint, being the primary bearer of the body weight, plays a vital role in mobility. Continuous monitoring of the knee joint can potentially provide important information related to knee health and mobility which can be used for health assessment, early diagnoses of mobility-related problems, and monitoring recovery from injury or surgery. Therefore, we developed a simple, low-cost multi-sensor-based smart wearable device to monitor and assess the knee joint and mobility. The system is composed of miniaturized sensors (motion, temperature, pressure and galvanic skin response) to measure acceleration, angular velocity, skin temperature, muscle pressure and sweat rate of the knee joint during different activities. A database is constructed from 70 healthy adults aged 18-86 years that contains sensor data measured using the proposed knee joint monitoring system. To extract key knee and gait features from the datasets, we employed computationally efficient methods such as complementary filter and wavelet packet decomposition. The variations in the characteristics of the obtained parameters were analyzed in terms of gender and age groups. This simple, easy-to-use, cost-effective, non-invasive and unobtrusive knee monitoring system can be used for real-time monitoring, evaluation and early diagnoses of joint disorders, fall detection, mobility monitoring and rehabilitation.

Recent advances in micro-electromechanical systems technology have enabled the evolution of miniature, low-power, and high-performance inertial motion sensors that are commonly found in most present-day smart gadgets. Furthermore, high-speed and power-efficient communication and computing technologies may enable these sensors to potentially pave the way for home-based remote monitoring and assessment of human health in the imminent age of new technologies such as Smart Home, internet-of-things, and internet-of-everything. Continuous monitoring of lower-limb joints in a wearable platform is such an application that may potentially enable the tele-rehabilitation of patients with motor impairment, gait abnormalities, and joint injuries through quantitative rather than observational analysis of gait health. In this work, we designed, implemented, and validated a two-stage sensor fusion algorithm to estimate lower-limb joint angles in real-time. The drift in the cumulatively integrated gyroscope data was estimated in real-time using a gradient descent approach that was subsequently used to correct the inclination of the sensors. The roll and pitch angles thus obtained for each sensor mounted above and below the joint were then fused in the second stage to obtain a real-time estimate of joint angle by exploiting a gradient descent method. Since the joint angles were estimated primarily from the gyroscope data and without incorporating any magnetic field measurement, the joint angles thus obtained were least affected by the external acceleration and are insensitive to magnetic disturbances. The performance of the proposed algorithm was validated with a publicly available dataset and in the presence of simulated external acceleration.

Advancements in the micro-electromechanical systems technology have enabled the realization of small-size, high-performance inertial motion and magnetic field sensors that are embedded in most modern-day smart gadgets. These sensors, when coupled with the high-speed computing and communication technologies may potentially enable in-home monitoring and assessment of human health in the forthcoming age of Smart home technologies, internet-of-thing, and internet-of-everything. However, because the sensor’s orientation is generally arbitrary, this may cause erroneous results of important health parameters such as gait speed and range of motion of the knee joint. Therefore, it is important that the sensor’s measurements be corrected for orientation. In this work, we designed, implemented, and validated a three-stage sensor fusion algorithm. A gradient descent approach was exploited to estimate the drift in and subtract it from the cumulatively integrated gyroscope data to obtain the orientation in real time. The roll and pitch angles were obtained from the first stage, whereas the second and third stages outputs a coarse and fine estimate of yaw angle, respectively. Since the estimation was obtained primarily from the gyroscope data, the estimated orientation was least affected by the external acceleration and magnetic disturbances. The performance of the proposed algorithm was validated with a publicly available dataset, and in presence of external acceleration and magnetic disturbances. Finally, some key gait parameters were derived from the gait measurements using the proposed filter that showed high conformity to the ground-truth values.

Tailoring the precise construction of non-precious metals and carbon-based heterogeneous catalysts for electrochemical oxygen evolution reaction (OER) and methanol oxidation reaction (MOR) is crucial for energy conversion applications. Herein, this work reports the composite of Ni doped Fe2 O3 (Ni-Fe2 O3 ) with mildly oxidized multi-walled CNT (O-CNT) as an outstanding Mott-Schottky catalyst for OER and MOR. O-CNT acts as a co-catalyst which effectively regulates the charge transfer in Ni-Fe2 O3 and thus enhances the electrocatalytic performance. Ni-Fe2 O3 /O-CNT exhibits a low onset potential of 260 mV and overpotential 310 mV @ 10 mA cm-2 for oxygen evolution. Being a Mott-Schottky catalyst, it achieves the higher flat band potential of -1.15 V with the carrier density of 0.173×1024 cm-3 . Further, in presence of 1 M CH3 OH, it delivers the MOR current density of 10 mA cm-2 at 1.46 V vs. RHE. The excellent electrocatalytic OER and MOR activity of Ni-Fe2 O3 /O-CNT could be attributed to the synergistic interaction between Ni-doped Fe2 O3 and O-CNT.

In the crystallization of polymers, besides monolamellar polymer crystals, stacks of correlated lamellae with a unique orientation and signatures of single crystals have often been observed. However, we still lack a generic criterion for such stacking, that is, vertical growth of polymer crystals. Here, by employing self-induced nucleation on the fold surface of a basal lamella for generating appropriate seeds, we identify experimental conditions allowing for a controlled formation of stacks of crystalline lamellae of a block copolymer. Adopting a two-step crystallization procedure, we decoupled nucleation and growth conditions of stacked lamellae and thereby favored vertical growth of polymer crystals in thin films. A sufficient reservoir of molten polymers in combination with slow lateral growth of the basal lamella is required for observing the formation of stacks of correlated lamellae. Taking this path, we were able to form stacks reaching heights of about 10 times the initial film thickness.

Background Thousands of Coronavirus Disease 2019 (COVID-19) patients have been discharged from hospitals Persistent follow-up studies are required to evaluate the prevalence of post-COVID-19 fibrosis. Methods This study involves 462 laboratory-confirmed patients with COVID-19 who were admitted to Shenzhen Third People’s Hospital from January 11, 2020 to April 26, 2020. A total of 457 patients underwent thin-section chest CT scans during the hospitalization or after discharge to identify the pulmonary lesion. A total of 287 patients were followed up from 90 to 150 days after the onset of the disease, and lung function tests were conducted about three months after the onset. The risk factors affecting the persistence of pulmonary fibrosis were identified through regression analysis and the prediction model of the persistence of pulmonary fibrosis was established. Results Parenchymal bands, irregular interfaces, reticulation and traction bronchiectasis were the most common CT features in all COVID-19 patients. During the 0–30, 31–60, 61–90, 91–120 and > 120 days after onset, 86.87%, 74.40%, 79.56%, 68.12% and 62.03% patients developed with pulmonary fibrosis and 4.53%, 19.61%, 18.02%, 38.30% and 48.98% patients reversed pulmonary fibrosis, respectively. It was observed that Age, BMI, Fever, and Highest PCT were predictive factors for sustaining fibrosis even after 90 days from onset. A predictive model of the persistence with pulmonary fibrosis was developed based-on the Logistic Regression method with an accuracy, PPV, NPV, Sensitivity and Specificity of the model of 76%, 71%, 79%, 67%, and 82%, respectively. More than half of the COVID-19 patients revealed abnormal conditions in lung function after 90 days from onset, and the ratio of abnormal lung function did not differ on a statistically significant level between the fibrotic and non-fibrotic groups. Conclusions Persistent pulmonary fibrosis was more likely to develop in patients with older age, higher BMI, severe/critical condition, fever, a longer viral clearance time, pre-existing disease and delayed hospitalization. Fibrosis developed in COVID-19 patients could be reversed in about a third of the patients after 120 days from onset. The pulmonary function of less than half of COVID-19 patients could turn to normal condition after three months from onset. An effective prediction model with an average area under the curve (AUC) of 0.84 was established to predict the persistence of pulmonary fibrosis in COVID-19 patients for early diagnosis.

The aging population is projected to rise significantly due to continuous improvements in healthcare, personal and environmental hygiene, nutrition, and education. This large aging demographic may cause adverse socio-economic impacts in terms of the costs associated with healthcare and social services. In order to support the healthcare needs of the elderly in a cost-effective manner, affordable, non-invasive, easy-to-use, and reliable predictive diagnostic and monitoring solutions are required. Therefore, walking or gait, being a good indicator of our overall health status may be exploited as a simple, noninvasive, and reliable metric for health assessment. In this paper, we report on a simple, low-cost, and non-invasive gait analyzer that can quantitatively identify the healthy gait corresponding to gender and age, and can thereby evaluate an individual’s gait with respect to the baseline characteristics of his/her peer group. The analyzer uses low-cost, wireless, and miniature micro-electromechanical sensor-based inertial motion sensors to obtain acceleration and angular velocity of walking from both legs. Upon constructing a database of walking signals from 74 healthy subjects aged 18–65 years, we employed the computationally efficient discrete wavelet packet analysis method to extract a set of temporal, statistical, and energy features. The features obtained from the apparently healthy subjects were classified using the support vector machine, forming two distinct clusters in the baseline gait characteristics corresponding to gender and age. This simple and inexpensive gait analyzer can potentially be transformed into a portable and continual remote monitoring tool to evaluate and early diagnose the decline of the musculoskeletal or cognitive health of the user, thus facilitating healthy aging at home.

Background: Thousands of the Coronavirus Disease 2019 (COVID-19) patients have been discharged from hospitals, persistent follow-up studies are required to evaluate the prevalence of post-COVID-19 fibrosis.Methods: This study involves 462 laboratory confirmed patients with COVID-19 who were admitted to Shenzhen Third People’s Hospital from January 11, 2020 to April 26, 2020. A total of 457 patients underwent thin-section chest CT scans during the hospitalization or after discharge to identify the pulmonary lesion. A total of 287 patients were followed up from 90 days to 150 days after the onset of the disease, and lung function tests were conducted in about three months after the onset. The risk factors affecting the persistence of pulmonary fibrosis were identified through regression analysis and the prediction model of the persistence of pulmonary fibrosis was established.Results: Parenchymal bands, irregular interfaces, reticulation and traction bronchiectasis were the most common CT features in all COVID-19 patients. During the 0-30, 31-60, 61-90, 91-120 and >120 days after onset, 86.87%, 74.40%, 79.56%, 68.12% and 62.03% patients developed with pulmonary fibrosis and 4.53%, 19.61%, 18.02%, 38.30% and 48.98% patients reversed pulmonary fibrosis, respectively. It was observed that Age, BMI, Fever, and Highest PCT were predictive factors for sustaining fibrosis even after 90 days from onset. A predictive model of the persistence with pulmonary fibrosis was developed based-on the Logistic Regression method with an accuracy, PPV, NPV, Sensitivity and Specificity of the model of 76%, 71%, 79%, 67%, and 82%, respectively. More than half of COVID-19 patients revealed abnormal condition in lung function after 90 days from onset, and the ratio of abnormal lung function did not differ on a statistically significant level between the fibrotic and non-fibrotic groups.Conclusions: Persistent pulmonary fibrosis was more likely to develop in patients with older age, high BMI, severe/critical condition, fever, long time to turn the viral RNA negative, pre-existing disease and delay to admission. Fibrosis developed in COVID-19 patients could be reversed in about a third of the patients after 120 days from onset. The pulmonary function of less than half of COVID-19 patients could turn to normal condition after three months from onset. An effective prediction model with an average Area Under the Curve (AUC) of 0.84 was established to predict the persistence of pulmonary fibrosis in COVID-19 patients for early diagnosis.

Background Remdesivir, a nucleotide analogue prodrug that inhibits viral RNA polymerases, has shown in vitro activity against SARS-CoV-2. Methods We provided remdesivir on a compassionate-use basis to patients hospitalized with Covid-19, the illness caused by infection with SARS-CoV-2. Patients were those with confirmed SARS-CoV-2 infection who had an oxygen saturation of 94% or less while they were breathing ambient air or who were receiving oxygen support. Patients received a 10-day course of remdesivir, consisting of 200 mg administered intravenously on day 1, followed by 100 mg daily for the remaining 9 days of treatment. This report is based on data from patients who received remdesivir during the period from January 25, 2020, through March 7, 2020, and have clinical data for at least 1 subsequent day. Results Of the 61 patients who received at least one dose of remdesivir, data from 8 could not be analyzed (including 7 patients with no post-treatment data and 1 with a dosing error). Of the 53 patients whose data were analyzed, 22 were in the United States, 22 in Europe or Canada, and 9 in Japan. At baseline, 30 patients (57%) were receiving mechanical ventilation and 4 (8%) were receiving extracorporeal membrane oxygenation. During a median follow-up of 18 days, 36 patients (68%) had an improvement in oxygen-support class, including 17 of 30 patients (57%) receiving mechanical ventilation who were extubated. A total of 25 patients (47%) were discharged, and 7 patients (13%) died; mortality was 18% (6 of 34) among patients receiving invasive ventilation and 5% (1 of 19) among those not receiving invasive ventilation. Conclusions In this cohort of patients hospitalized for severe Covid-19 who were treated with compassionate-use remdesivir, clinical improvement was observed in 36 of 53 patients (68%). Measurement of efficacy will require ongoing randomized, placebo-controlled trials of remdesivir therapy. (Funded by Gilead Sciences.)

Background: Thousands of the Coronavirus Disease 2019 (COVID-19) patients have been discharged from hospitals, long-term follow-up studies are required to evaluate the prevalence of post-COVID-19 fibrosis.Methods: This study involves 462 laboratory confirmed patients with COVID-19 who were admitted to Shenzhen Third People’s Hospital from January 11, 2020 to April 26, 2020. A total of 457 patients underwent thin-section chest CT scans during the hospitalization or after discharge to identify the pulmonary lesion. A total of 289 patients were followed up from 90 days to 150 days after the onset of the disease.Results: Parenchymal bands, irregular interfaces, meshwork and traction bronchiectasis were the most common CT features in all COVID-19 patients. 86.87%, 74.40%, 79.56%, 68.12% and 62.03% patients developed with pulmonary fibrosis and 4.53%, 19.61%, 18.02%, 38.30% and 48.98% patients reversed pulmonary fibrosis during the 0-30, 31-60, 61-90, 91-120 and >120 days after onset, respectively. It was observed that Age, BMI, Fever, and Highest PCT were predictive factors for sustaining fibrosis even after 90 days from onset. A predictive model of the persistence with pulmonary fibrosis was developed based-on the Logistic Regression method with an accuracy, PPV, NPV, Sensitivity and Specificity of the model of 76%, 71%, 79%, 67%, and 82%, respectively. Only a fraction of COVID-19 patients suffered with abnormal lung function after 90 days from onset, and the ratio of abnormal lung function did not differ on a statistically significant level between the fibrotic and non-fibrotic groups.Conclusions: Long-term pulmonary fibrosis was more likely to develop in patients with older age, high BMI, severe/critical condition, fever, long time to turn the viral RNA negative, pre-existing disease and delay to admission. Fibrosis developed in COVID-19 patients could be reversed in about a half of the patients after 120 days from onset. The pulmonary function of most of COVID-19 patients with pulmonary fibrosis could turn to normal condition after three months from onset. An effective prediction model with an average Area Under the Curve (AUC) of 0.84 was established to predict the persistence of pulmonary fibrosis in COVID-19 patients for early diagnosis.

Most theoretical concepts of polymer crystallization have evolved around monolamellar single crystals as model systems. However, such approaches do not account for an important and unique aspect of crystallization of long flexible molecules: the correlated stacking of lamellar crystals. In our experimental work, we focus on the growth kinetics of such stacks of lamellae in thin films of poly(nonadecane methylphosphonate). Interestingly, concurrent with a decrease in lateral lamellar growth, we observed an increase in vertical growth, that is, an increase in the number of stacked crystalline lamellae. Intriguingly, in contrast to lateral lamellar growth, the rate of such vertical growth increased with decreasing degree of undercooling. Moreover, we show the possibility of forming three-dimensional polymer quasi-single crystals. Some of the formed stacks of lamellar crystals were about 100 times thicker than the initial film; that is, they had a thickness of about 20 times the contour length of the polymer ...

We report novel morphologies with periodic height modulations of isotactic polystyrene (iPS) crystals, resulting from alternating stacks of correlated lamellae. Systematic experiments were performed on iPS films of several thicknesses (h) for varying degrees of undercooling, ΔT = Tm∞ – TC, where Tm∞ and TC are the equilibrium melting temperature and the crystallization temperature, respectively. We demonstrate that the spatial period (λ), i.e., the mean distance between neighboring stacks of lamellae, exhibits a power-law dependence on h and an exponential dependence on 1/ΔT. We propose that self-induced nucleation of stacked layers caused periodic deviation in the growth rate of iPS crystals, yielding periodic height modulations.

Superoleophobic surfaces exhibiting tunable wettability are prepared by the combination of simple spray coating of Ultra Violet (UV) responsive titania nanoparticles and a low surface energy coating of a self-assembled monolayer (SAM) of 1H,1H,2H,2H-perflurodecyltrichlorosilane (PFDTS). Spray coating creates random micron-sized roughness with reentrant geometry, a necessary requirement for the superoleophobic surface, and a porous network at the nanometer size level, confirmed by the field emission scanning electron microscope (FE-SEM) images. By employing the rough surface and a low surface energy monolayer, the substrates possess superhydrophobicity with a water (γ = 72 mN m−1) contact angle of 163° and superoleophobicity with a decane (γ = 23 mN m−1) contact angle of 144°. Wettability of these surfaces is completely reversed to the superoleophilic state upon 6 h of UV irradiation. A quantitative X-ray photoelectron spectroscopy (XPS) analysis has confirmed the mechanism of decomposition of PFDTS molecules on the superoleophilic surfaces via interaction with the defect Ti3+ states of titania upon UV exposure. Furthermore, the superoleophobicity is restored to complete the transition cycle by changing the surface chemistry of the UV exposed surface via annealing and regrafting of the PFDTS monolayer.

Semicrystalline aliphatic polyphosphoesters can be obtained in a one-step approach by polyesterification of readily available bio-based long-chain diols with dichlorophosphorus compounds. Nonadecane-1,19-diol and tricosane-1,23-diol with respectively methylphosphonic dichloride or phenyl dichlorophosphate yield polymers (PPE19Me, PPE23Me, PPE19(OPh), and PPE23(OPh)) with molecular weights Mn up to 3 × 104 g mol–1. DSC analysis of these polymers and a C12 analogue reveal significantly enhanced crystallinities and melting points (up to Tm = 87 °C) with increasing methylene sequence length. DMA on injection-molded samples shows glass transitions at −19 °C (PPE19Me) and −12 °C (PPE23Me). Single crystals of PPE19Me accommodate a single C19 repeat unit, as concluded from a lamella thickness of only 3 nm thick determined by AFM. Hydrolytic degradation of solid polymer samples under ambient conditions occurred only to a minimal extent over three months by hydrolysis of very small amounts of in-chain anhydride def...

Processing bodies (PB) and stress granules (SG) are prominent examples of sub-cellular, membrane-less compartments that are observed under physiological and stress conditions, respectively. We observe that the trimeric PB protein DCP1A rapidly (within ~10 s) phase-separates in mammalian cells during hyperosmotic stress and dissolves upon isosmotic rescue (over ~100 s) with minimal impact on cell viability even after multiple cycles of osmotic perturbation. Strikingly, this rapid intracellular hyperosmotic phase separation (HOPS) correlates with the degree of cell volume compression, distinct from SG assembly, and is exhibited broadly by homo-multimeric (valency ≥ 2) proteins across several cell types. Notably, HOPS sequesters pre-mRNA cleavage factor components from actively transcribing genomic loci, providing a mechanism for hyperosmolarity-induced global impairment of transcription termination. Together, our data suggest that the multimeric proteome rapidly responds to changes in hydration and molecular crowding, revealing an unexpected mode of globally programmed phase separation and sequestration.

Here, a well crystalline 3D flower-like structured MoS2 (~420 nm) has been successfully synthesized on a large scale by a simple hydrothermal technique. The evolution of morphology in the formation process has also been investigated. The crystallinity, purity, and morphology of the sample are characterized by powder X-ray diffraction, Fourier-transform infrared spectroscopy, fieldemission scanning electron microscopy (FESEM), and transmission electron microscopy (TEM) techniques. The FESEM and TEM images reveal that the sample exhibits a uniform 3D flower-like microsphere shape with folded nanosheets, which are stretched out along the edge of the microsphere. The electrochemical performance of the sample has been investigated by cyclic voltammogram, galvanostatic charge-discharge, and electrochemical impedance spectroscopy studies. The results of the electrochemical analysis suggest that the material delivers a maximum specific capacitance (Csp) of 350 F/g at a discharge current density of 0.25 A/g with energy density 17.5 Wh/kg. It also exhibits good capability and excellent cyclic stability (94% capacity retention after 1,000 cycles in 1 A/g) owing to the coupling effect of electrical conductivity with the interesting morphology and larger active surface area. Hence, the sample may be used as a promising electrode material for high-performance energy storage devices.

Electrocardiography (ECG) is the most common and extensively used vital sign monitoring method in modern healthcare systems. Different designs of ambulatory ECG systems were developed as alternatives to the commonly used 12-lead clinical ECG systems. These designs primarily focus on portability and user convenience, while maintaining signal integrity and lowering power consumption. Here, a wireless ECG monitoring system is developed using flexible and dry capacitive electrodes for long-term monitoring of cardiovascular health. Our capacitive-coupled dry electrodes can measure ECG signals over a textile-based interface material between the skin and electrodes. The electrodes are connected to a data acquisition system that receives the raw ECG signals from the electrodes and transmits the data using Bluetooth to a computer. A software application was developed to process, store, and display the ECG signal in real time. ECG measurements were obtained over different types of textile materials and in the presence of body movements. Our experimental results show that the performance of our ECG system is comparable to other reported ECG monitoring systems. In addition, to put this research into perspective, recent ambulatory ECG monitoring systems, ECG systems-on-chip, commercial ECG monitoring systems, and different state-of-the-art ECG systems are reviewed, compared, and critically discussed.

The world’s population is aging: the expansion of the older adult population with multiple physical and health issues is now a huge socio-economic concern worldwide. Among these issues, the loss of mobility among older adults due to musculoskeletal disorders is especially serious as it has severe social, mental and physical consequences. Human body joint monitoring and early diagnosis of these disorders will be a strong and effective solution to this problem. A smart joint monitoring system can identify and record important musculoskeletal-related parameters. Such devices can be utilized for continuous monitoring of joint movements during the normal daily activities of older adults and the healing process of joints (hips, knees or ankles) during the post-surgery period. A viable monitoring system can be developed by combining miniaturized, durable, low-cost and compact sensors with the advanced communication technologies and data processing techniques. In this study, we have presented and compared different joint monitoring methods and sensing technologies recently reported. A discussion on sensors’ data processing, interpretation, and analysis techniques is also presented. Finally, current research focus, as well as future prospects and development challenges in joint monitoring systems are discussed.

Advancements in medical science and technology, medicine and public health coupled with increased consciousness about nutrition and environmental and personal hygiene have paved the way for the dramatic increase in life expectancy globally in the past several decades. However, increased life expectancy has given rise to an increasing aging population, thus jeopardizing the socio-economic structure of many countries in terms of costs associated with elderly healthcare and wellbeing. In order to cope with the growing need for elderly healthcare services, it is essential to develop affordable, unobtrusive and easy-to-use healthcare solutions. Smart homes, which incorporate environmental and wearable medical sensors, actuators, and modern communication and information technologies, can enable continuous and remote monitoring of elderly health and wellbeing at a low cost. Smart homes may allow the elderly to stay in their comfortable home environments instead of expensive and limited healthcare facilities. Healthcare personnel can also keep track of the overall health condition of the elderly in real-time and provide feedback and support from distant facilities. In this paper, we have presented a comprehensive review on the state-of-the-art research and development in smart home based remote healthcare technologies.

Life expectancy in most countries has been increasing continually over the several few decades thanks to significant improvements in medicine, public health, as well as personal and environmental hygiene. However, increased life expectancy combined with falling birth rates are expected to engender a large aging demographic in the near future that would impose significant burdens on the socio-economic structure of these countries. Therefore, it is essential to develop cost-effective, easy-to-use systems for the sake of elderly healthcare and well-being. Remote health monitoring, based on non-invasive and wearable sensors, actuators and modern communication and information technologies offers an efficient and cost-effective solution that allows the elderly to continue to live in their comfortable home environment instead of expensive healthcare facilities. These systems will also allow healthcare personnel to monitor important physiological signs of their patients in real time, assess health conditions and provide feedback from distant facilities. In this paper, we have presented and compared several low-cost and non-invasive health and activity monitoring systems that were reported in recent years. A survey on textile-based sensors that can potentially be used in wearable systems is also presented. Finally, compatibility of several communication technologies as well as future perspectives and research challenges in remote monitoring systems will be discussed.

Surface micromachined, electrostatically actuated microswitches have been developed at Northeastern University. Microswitches with gold contacts typically have an initial contact resistance of the order of 0.1 Ω over the first 10 5 cycles of lifetime while cold-switching 4 mA, and have a current handling capability of about 20 mA. In general, the contact resistance decreases over the first few thousand switch cycles, and degrades progressively when the switches are cycled beyond approximately 10 6 cycles. In this work, the microswitch contact resistance is studied on the basis of a clean metal contact resistance model. Comparison of the measured contact resistance (measured as a function of contact force) with the characteristics predicted by the model shows approximate agreement. The discrepancies between the model characteristics and measurements are discussed briefly.

Micromechanical switches and relays realized by a simple surface micromachining process are presented. The devices use a nickel cantilever beam and gold-to-gold electrical contact, and are electrostatically actuated. They have lifetimes exceeding 109 cycles, and a current handling capability of 150 mA.

Micromechanical switches have been fabricated in electroplated nickel using a four-level surface micromachining process. The simplest devices are configured with three terminals, a source, a drain, and a gate and are 30 /spl mu/m wide, 1 /spl mu/m thick, and 65 /spl mu/m long. A voltage applied between the gate and source closes the switch, connecting the source to the drain. Devices switch more than 10/sup 9/ cycles before failure and exhibit long-lifetime hot switching currents up to 5 mA. The initial contact resistance is less than 50 m/spl Omega/. The breakdown (stand-off) voltage between the source and the drain is greater than 100 V and the off-current is less than 20 fA at 100 V.

MEMS are becoming important building blocks for a variety of military and commercial applications including phase shifters, electronically scanned antennas, switched filters, Automatic Test Equipment, instrumentation, cell phones and smart antennas. Low power consumption, large ratio of off-impedance to on-impedance, extreme linearity and the ability to be integrated with other electronics, make MEMS switches attractive. Wafer Level Packaging and contact metallurgy have contributed to the steady progress that has been made in improving RF MEMS switch reliability during the past five years. Extensive lifetime and RF testing has been conducted on an electrostatically actuated broadband ohmic microswitch under the auspices of the DARPA HERMIT program. Final testing led to a median cycle to failure greater than 1 trillion cycles with the longest recorded lifetimes exceeding 1.5 trillion switch cycles before the test was halted after 30 continuous months. Testing was also conducted on a high-power MEMS switch that demonstrated greater than 200 billion switch cycles with 10W of cold-switched RF power at X-Band. Finally, a series of environmental tests including temperature cycling, humidity testing, and mechanical shock and vibration were successfully conducted per MIL-STD-883E.

We discuss the source of random telegraph signal (RTS) behavior in photodiodes, metal-oxide-semiconductor (MOS) transistors and active pixel sensors (APS). First, a detailed review on the magnitude and the time constants of RTS noise observed in state-of-the art small-pitch imagers will be presented. Second, the impact of RTS noise on the quality of the images obtained from MOS imagers will be discussed, with a focus on the noise requirements for biomedical imaging applications. Finally, our experimental results will be discussed and some ideas on how to deal with RTS noise in silicon imagers will be described based on the RTS noise analyses.

Broadband, true time delay phase shifters based on MEMS switches provide the high instantaneous bandwidth desired for applications such as multi-frequency antenna arrays with multiple functions such as radar, communications, and ECM. MEMS based phase shifters offer significant performance advantages compared to technologies using PIN diode or MESFET switches including high linearity that does not limit the dynamic range of the receiver in a crowded signal environment. Furthermore, MEMS phase shifters offer a combination of low RF insertion loss and low switch control power consumption that is unmatched by PIN diode or MESFET technologies, giving the MEMS phase shifters a decided advantage at reducing prime power consumption in airborne or space based systems. Radant MEMS Inc., employing its high power 10 Watt MEMS switch with a demonstrated 1 trillion cycle lifetime, designed, fabricated and tested a 6-bit, 5 Watt, true time delay, 1–6 GHz, MEMS phase shifter that, with the exception of the three longest delay lines, was integrated on a single silicon die. This compact, low cost phase shifter is hermetically sealed using the same wafer capping process now employed for Radant's MEMS switches.

A multi-asperity model of the contact resistance in a MEMS microswitch has been developed which includes the effects of elastic and plastic deformation, adhesion, and constrictive resistance. The number of asperities in contact is small enough that a discrete distribution of asperity heights is used. Adhesion produces significant hysteresis in the contact resistance vs. contact force characteristics. Due to the combined effects of plasticity and adhesion, the surface profile changes during the first load/unload cycle. Measurements of the contact resistance as a function of actuation voltage show good qualitative agreement with the model.

Electrostatically actuated microswitches and relays have been developed at Northeastern University and Analog Devices, Inc. Here, we report a steady-state thermal-electrical finite element model of microswitches with gold-gold contacts. The modeling results show that in a microswitch with a typical geometry, the thermal constriction occurs in the thin film trace leading up to the contact, and not at the contact interface. The model correctly predicts the switch voltage at which the drain trace melts, but underestimates the switch resistance, and therefore overestimates the failure current. SEM images indicate that the contact area increases significantly with current.

In the future, MEMS switches will be important building blocks for designing phase shifters, smart antennas, cell phones and switched filters for military and commercial markets, to name a few. Low power consumption, large ratio of off-impedance to on-impedance and the ability to be integrated with other electronics makes MEMS switches an attractive alternative to other mechanical and solid-state switches. Radant MEMS has developed an electrostatically actuated broadband ohmic microswitch that has applications from DC through the microwave region. The microswitch is a 3-terminal device based on a cantilever beam and is fabricated using an all-metal, surface micromachining process. It operates in a hermetic environment obtained through a wafer-bonding process. We have developed PC-based test stations to cycle switches and measure lifetime under DC and RF loads. Best-case lifetimes of 10 11 cycles have been achieved in T0-8 cans (a precursor to our wafer level cap) while greater than 10 10 cycles have been achieved in the wafer level package. Several switches from different lots have been operated to 10 10 cycles. Current typical lifetime exceeds 2 billion cycles and is limited by contact stiction resulting in stuck-closed failures. Stuck-closed failures can be intermittent with a large number of switches continuing to operate with occasional sticks beyond several billion cycles. To eliminate contact stiction, we need to better control the ambient gas composition in the die cavity. We expect lifetime to improve as we continue to develop and optimize the wafer capping process. We present DC and RF lifetime data under varying conditions.

A multi-asperity model of the contact resistance in a MEMS microswitch has been developed. This model includes the effects of elastic and plastic deformation, adhesion, and scale-dependent constrictive resistance. The number of asperities in contact is small enough that a discrete, rather than a continuous, distribution of asperity heights is used. Due to the combined effects of plasticity and adhesion, the surface profile changes with repeated load and unload cycles. Furthermore, adhesion produces significant hysteresis in the contact resistance vs. contact force characteristics. Measurements of the contact resistance as a function of actuation voltage show good qualitative agreement with the model.Copyright © 2003 by ASME

Electrostatically actuated micromechanical switches have been reported in earlier work by the authors. In the present work, a simple contact resistance model of the microswitch is discussed. Preliminary contact resistance measurements are presented, and compared with the modeled contact resistance characteristics.

Micromechanical switches have been fabricated in electroplated nickel using a four-level surface micromachining process. The simplest devices are configured with three terminals, a source, a drain, and a gate and are 30 µm wide, 1 µm thick, and 65 µm long. A voltage applied between the gate and the source closes the switch, connecting the source to the drain. Devices operate for more than 109 cycles in a nitrogen ambient before failure and have an initial contact resistance of less than 50 mΩ. The threshold voltages for these devices are between 30 V and 200 V. Long lifetimes are achieved with a current of 30 mA. The breakdown (stand-off) voltage between the source and the drain is greater than 100 V and the off-impedance exceeds 1012Ω. The modeling of these switches includes a structural model of the beam and a contact resistance model for the electrical contact. Preliminary contact resistance measurements are presented and compared with the modeled contact resistance characteristics.

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