A CMOS Integrator-Based Clock-Free Time-to-Digital Converter for Home-Monitoring LiDAR Sensors

This paper presents a nine-bit integrator-based time-to-digital converter (I-TDC) realized in a 180 nm CMOS technology for the applications of indoor home-monitoring light detection and ranging (LiDAR) sensors. The proposed I-TDC exploits a clock-free configuration so as to discard clock-related dynamic power consumption and some notorious issues such as skew, glitch, and synchronization. It consists of a one-dimensional (1D) flash TDC to generate coarse-control codes and an integrator with a peak detection and hold (PDH) circuit to produce fine-control codes. A thermometer-to-binary converter is added to the 1D flash TDC, yielding four-bit coarse codes so that the measured detection range can be represented by nine-bit digital codes in total. Test chips of the proposed I-TDC demonstrate the measured results of the 53 dB dynamic range, i.e., the maximum detection range of 33.6 m and the minimum range of 7.5 cm. The chip core occupies the area of 0.14 × 1.4 mm2, with the power dissipation of 1.6 mW from a single 1.2-V supply.

A Retrospective Study on “Effectiveness of Remote Patient Monitoring in Covid-19 patients"

Corona virus disease19 has spread over the world, affecting millions of people. It has put enormous strain on the global healthcare system. Due to frequent mutations, the pandemic is spreading rapidly. The world requires a technology that will facilitate the effective diagnosis, treatment, and discharge of COVID19 patients. A model like remote patient monitoring [RPM] makes it easier to handle Covid 19 patients. RPM helps in remotely diagnosis, treatment, as well as allowing for prompt interventions. The RPM makes use of mobile technology and IoT platforms to take clinical interventions. In this study out of 151 covid19 positive subjects 91% of them were shifted to home monitoring within 5 days of MVM monitoring with few readmissions. The study investigated the effectiveness of RPM in the Indian healthcare system, as well as the performance and usability of the Vigocare mobile application by patients and doctors.

Protocol for detecting unrecognized sleep apnea in patients with atrial fibrillation by a home-monitoring device: the DAN-APNO study

Background Determining the presence of modifiable risk factors for atrial fibrillation (AF), such as sleep apnea is of clinical importance due to the potential impact targeting these risk factors can have on the progression and burden of AF. Using new digital-based technology is a promising solution to the underreporting of sleep apnea highlighted by academical societies in recent years. The aim of this study is to report the prevalence and severity of sleep apnea in patients with AF and, secondarily, assess the accuracy and feasibility of a new home-screening device for sleep apnea (NightOwl™ by Ectosense). Methods DAN-APNO is a cross-sectional study at the Department of Cardiology, Herlev-Gentofte Hospital recruiting patients with AF referred to anticoagulation initiation aged 18 to 90 years without known sleep apnea. At least 150 patients will be recruited and undergo medical history, clinical evaluation, several sleep-apnea questionnaires, and a sleep-recording evaluation for four nights with sleep apnea home-monitoring device NightOwl™. Additionally, the first 20 participants and participants with moderate-severe sleep apnea by screening are referred to cardio-respiratory monitoring (CRM). This clinical evaluation allows the comparison of standard evaluation method and the NightOwl™. Clinical measures include Apnea–Hypopnea Index (AHI), Oxygen Desaturation Index (ODI), pulse rate, as well as questionaries about sleep apnea assessment and the clinical feasibility of the NightOwl™ device. Main outcomes comprise analysis of the prevalence and severity of sleep apnea, and clinical and demographic predictors of moderate and severe sleep apnea. In addition, correlation analyses for accuracy measures between CRM and NightOwl™ will be conducted along with patient ease-of-use and satisfaction questionnaires. Discussion This study is limited by selection bias; only patients with atrial fibrillation from anticoagulation clinic is asked to participate, which could limit the generalizability of our results. However, this study aims to test whether a miniaturized simple home-monitoring device for detecting sleep apnea in patients with AF potentially can evaluate sleep apnea more conveniently and easier. Trial Registration The study is registered the 18-02-2021 at clinicaltrials.gov with registration number: NCT04760002.

Design of Monitoring and Controlling System for Smart Home

An intelligent lifestyle has become a hotspot for researchers and industries nowadays. The smart home monitoring and controlling system with the Arduino as the main controller is designed in this paper, combined with sensors, Wi-Fi, and cloud technologies. Various sensors collect household environmental information, such as indoor temperature and humidity, soil moisture, combustible gas concentration, and light intensity. The main controller processes the collected signals and automatically operates the devices, including a refrigeration equipment, water pump, buzzer, fan, stepping motor. The data can also be transmitted to the cloud platform through Wi-Fi for processing, and the home environment information and device can be remotely monitored and controlled by the cloud platform or smartphone APP.

Bionic for Training: Smart Framework Design for Multisensor Mechatronic Platform Validation

Home monitoring supports the continuous improvement of the therapy by sharing data with healthcare professionals. It is required when life-threatening events can still occur after hospital discharge such as neonatal apnea. However, multiple sources of external noise could affect data quality and/or increase the misdetection rate. In this study, we developed a mechatronic platform for sensor characterizations and a framework to manage data in the context of neonatal apnea. The platform can simulate the movement of the abdomen in different plausible newborn positions by merging data acquired simultaneously from three-axis accelerometers and infrared sensors. We simulated nine apnea conditions combining three different linear displacements and body postures in the presence of self-generated external noise, showing how it is possible to reduce errors near to zero in phenomena detection. Finally, the development of a smart 8Ws-based software and a customizable mobile application were proposed to facilitate data management and interpretation, classifying the alerts to guarantee the correct information sharing without specialized skills.

Home Monitoring for Fever: An Inexpensive Screening Method to Prevent Household Spread of COVID-19

The COVID-19 pandemic surge has exceeded testing capacities in many parts of the world. We investigated the effectiveness of home temperature monitoring for early identification of COVID-19 patients. Study Design: We compared home temperature measurements from a convenience sample of 1180 individuals who reported being test positive for SARS-CoV-2 to an age, sex, and location matched control group of 1249 individuals who had not tested positive. Methods: All individuals monitored their temperature at home using an electronic smartphone thermometer that relayed temperature measurements and symptoms to a centralized cloud based, de-identified data bank. Results: Individuals varied in the number of times they monitored their temperature. When temperature was monitored for over 72 hours fever (> 37.6 C or 99.7 F or a change in temperature of > 1 C or 1.8 F) was detected in 73% of test positive individuals, a sensitivity comparable to rapid SARS-CoV-2 antigen tests. When compared our control group the specificity of fever for COVID-19 was 0.70. However, when fever was combined with complaints of loss of taste and smell, difficulty breathing, fatigue, chills, diarrhea, or stuffy nose the odds ratio of having COVID-19 was sufficiently high as to obviate the need to employ RTPCR or antigen testing to screen for and isolate coronavirus infected cases. Conclusions - Our findings suggest that home temperature monitoring could serve as an inexpensive convenient screen for the onset of COVID-19, encourage earlier isolation of potentially infected individuals, and more effectively reduce the spread of infection in closed spaces.

Patients' and carers' experiences of, and engagement with remote home monitoring services for COVID-19 patients: a rapid mixed-methods study

Introduction: Remote home monitoring models were implemented during the COVID-19 pandemic to shorten hospital length of stay, reduce unnecessary hospital admission, readmission and infection, and appropriately escalate care. Within these models, patients are asked to take and record readings and escalate care if advised. There is limited evidence on how patients and carers experience these services. This study aimed to evaluate patient experiences of, and engagement with, remote home monitoring models for COVID-19. Methods: A rapid mixed-methods study in England. We conducted a cross-sectional survey and interviews with patients and carers. Interview findings were summarised using rapid assessment procedures sheets and grouping data into themes (using thematic analysis). Survey data were analysed using descriptive statistics. Results: We received 1069 surveys (18% response rate) and conducted interviews with patients (n=59) and carers (n=3). 'Care' relied on support from staff members, and family/friends. Patients and carers reported positive experiences and felt that the service and human contact reassured them and was easy to engage with. Yet, some patients and carers identified problems with engagement. Engagement was influenced by: patient factors such as health and knowledge, support from family/friends and staff, availability and ease-of-use of informational and material resources (e.g. equipment), and service factors. Conclusion: Remote home monitoring models place responsibility on patients to self-manage symptoms in partnership with staff; yet many patients required support and preferred human contact (especially for identifying problems). Caring burden and experiences of those living alone, and barriers to engagement should be considered when designing and implementing remote home monitoring services.

The impact of remote home monitoring of people with COVID-19 using pulse oximetry: a national population and observational study.

Background Remote home monitoring of people testing positive for COVID-19 using pulse oximetry was implemented across England during the Winter of 2020/21 to identify falling blood oxygen saturation levels at an early stage. This was hypothesised to enable earlier hospital admission, reduce the need for intensive care and improve survival. This study is an evaluation of the clinical effectiveness of the pre-hospital monitoring programme, COVID oximetry @home (CO@h). Methods We analysed relationships at a geographical area level between the extent to which people aged 65 or over were enrolled onto the programme and outcomes over the period between November 2020 to February 2021 Findings For every 10% increase in coverage of the programme, mortality was reduced by 2% (95% confidence interval: -4% to 1%), admissions increased by 3% (-1% to 7%), in-hospital mortality fell by 3% (-8% to 3%) and lengths of stay increased by 1.8% (-1.2% to 4.9%). None of these results are statistically significant. Interpretation There are several possible explanations for our findings. One is that the CO@h did not have the hypothesised impact. Another is that the low rates of enrolment and incomplete data in many areas reduced the chances of detecting any impact that may have existed. Also, CO@h has been implemented in many different ways across the country and these may have had varying levels of effect. Funding This is independent research funded by the National Institute for Health Research, Health Services & Delivery Research programme (RSET Project no. 16/138/17; BRACE Project no. 16/138/31) and NHSEI. NJF is an NIHR Senior Investigator. The views expressed in this publication are those of the authors and not necessarily those of the National Institute for Health Research or the Department of Health and Social Care.