Gene-Environment Interaction in the Era of Precision Medicine.

Innovative analytical frameworks are required to capture the complex gene-environment interactions. We investigate the insufficiency of commonly used models for disease genome analysis and suggest considering genetic interactions in complex diseases. For non-genetic factors, we study the emerging wearable technologies that have enabled quantification of physiological and environmental factors at an unprecedented breadth and depth. We propose a Bayesian framework to hierarchically model personalized gene-environmental interaction to enable precision health and medicine.

Machine learning and wearable devices of the future.

Machine learning (ML) is increasingly recognized as a useful tool in healthcare applications, including epilepsy. One of the most important applications of ML in epilepsy is seizure detection and prediction, using wearable devices (WDs). However, not all currently available algorithms implemented in WDs are using ML. In this review, we summarize the state of the art of using WDs and ML in epilepsy, and we outline future development in these domains. There is published evidence for reliable detection of epileptic seizures using implanted electroencephalography (EEG) electrodes and wearable, non-EEG devices. Application of ML using the data recorded with WDs from a large number of patients could change radically the way we diagnose and manage patients with epilepsy.

Twenty-four-hour patterns in electrodermal activity recordings of patients with and without epileptic seizures.

OBJECTIVE: Daytime and nighttime patterns affect the dynamic modulation of brain and body functions and influence the autonomic nervous system response to seizures. Therefore, we aimed to evaluate 24-hour patterns of electrodermal activity (EDA) in patients with and without seizures. METHODS: We included pediatric patients with (a) seizures (SZ), including focal impaired awareness seizures (FIAS) or generalized tonic-clonic seizures (GTCS), (b) no seizures and normal electroencephalography (NEEG), or (c) no seizures but epileptiform activity in the EEG (EA) during vEEG monitoring. Patients wore a device that continuously recorded EDA and temperature (TEMP). EDA levels, EDA spectral power, and TEMP levels were analyzed. To investigate 24-hour patterns, we performed a nonlinear mixed-effects model analysis. Relative mean pre-ictal (-30 min to seizure onset) and post-ictal (I: 30 min after seizure offset; II: 30 to 60 min after seizure offset) values were compared for SZ subgroups. RESULTS: We included 119 patients (40 SZ, 17 NEEG, 62 EA). EDA level and power group-specific models (SZ, NEEG, EA) (h = 1; P < .01) were superior to the all-patient cohort model. Fifty-nine seizures were analyzed. Pre-ictal EDA values were lower than respective 24-hour modulated SZ group values. Post hoc comparisons following the period-by-seizure type interaction (EDA level: χ2  = 18.50; P < .001, and power: χ2  = 6.73; P = .035) revealed that EDA levels were higher in the post-ictal period I for FIAS and GTCS and in post-ictal period II for GTCS only compared to the pre-ictal period. SIGNIFICANCE: Continuously monitored EDA shows a pattern of change over 24 hours. Curve amplitudes in patients with recorded seizures were lower as compared to patients who did not exhibit seizures during the recording period. Sympathetic skin responses were greater and more prolonged in GTCS compared to FIAS. EDA recordings from wearable devices offer a noninvasive tool to continuously monitor sympathetic activity with potential applications for seizure detection, prediction, and potentially sudden unexpected death in epilepsy (SUDEP) risk estimation.

Seizure forecasting and cyclic control of seizures.

Epilepsy is a unique neurologic condition characterized by recurrent seizures, where causes, underlying biomarkers, triggers, and patterns differ across individuals. The unpredictability of seizures can heighten fear and anxiety in people with epilepsy, making it difficult to take part in day-to-day activities. Epilepsy researchers have prioritized developing seizure prediction algorithms to combat episodic seizures for decades, but the utility and effectiveness of prediction algorithms has not been investigated thoroughly in clinical settings. In contrast, seizure forecasts, which theoretically provide the probability of a seizure at any time (as opposed to predicting the next seizure occurrence), may be more feasible. Many advances have been made over the past decade in the field of seizure forecasting, including improvements in algorithms as a result of machine learning and exploration of non-EEG-based measures of seizure susceptibility, such as physiological biomarkers, behavioral changes, environmental drivers, and cyclic seizure patterns. For example, recent work investigating periodicities in individual seizure patterns has determined that more than 90% of people have circadian rhythms in their seizures, and many also experience multiday, weekly, or longer cycles. Other potential indicators of seizure susceptibility include stress levels, heart rate, and sleep quality, all of which have the potential to be captured noninvasively over long time scales. There are many possible applications of a seizure-forecasting device, including improving quality of life for people with epilepsy, guiding treatment plans and medication titration, optimizing presurgical monitoring, and focusing scientific research. To realize this potential, it is vital to better understand the user requirements of a seizure-forecasting device, continue to advance forecasting algorithms, and design clear guidelines for prospective clinical trials of seizure forecasting.

Wearable Devices Are Well Accepted by Patients in the Study and Management of Inflammatory Bowel Disease: A Survey Study.

BACKGROUND: Wearable devices are designed to capture health-related and physiological data. They may be able to improve inflammatory bowel disease management and address evolving research needs. Little is known about patient perceptions for their use in the study and management of inflammatory bowel disease. AIMS: The aim of this survey study is to understand patient preferences and interest in wearable technology. METHODS: Consecutive adult patients who self-reported having inflammatory bowel disease were approached at the Susan and Leonard Feinstein Inflammatory Bowel Disease Center at the Mount Sinai Hospital to complete a 28-question survey. Reponses were analyzed with descriptive statistics. The Pearson Chi-square test and Fischer's exact test were used to determine the association between demographic and disease-related features and survey responses. RESULTS: Four hundred subjects completed the survey. 42.7% of subjects reported prior or current use of wearable devices. 89.0% of subjects believed that wearable devices can provide important information about their health, while 93.8% reported that they would use a wearable device if it could help their doctor manage their IBD. Subjects identified wrist-worn devices as the preferred device type and a willingness to wear these devices at least daily. CONCLUSIONS: Patients with inflammatory bowel disease believe that wearable devices can provide important information about their health and report a willingness to wear them frequently in research studies and as part the routine management of inflammatory bowel disease.

Frontiers in hemodialysis: Innovations and technological advances.

As increasing demand for hemodialysis (HD) treatment incurs significant financial burden to healthcare systems and ecological burden as well, novel therapeutic approaches as well as innovations and technological advances are being sought that could lead to the development of purification devices such as dialyzers with improved characteristics and wearable technology. Novel knowledge such as the development of more accurate kinetic models, the development of novel HD membranes with the use of nanotechnology, novel manufacturing processes, and the latest technology in the science of materials have enabled novel solutions already marketed or on the verge of becoming commercially available. This collaborative article reviews the latest advances in HD as they were presented by the authors in a recent symposium titled "Frontiers in Haemodialysis," held on 12th December 2019 at the Royal Society of Medicine in London.

Effect of Viscosity on the Formation of Porous Polydimethylsiloxane for Wearable Device Applications.

Medical devices, which enhance the quality of life, have experienced a gradual increase in demand. Various research groups have attempted to incorporate soft materials such as skin into wearable devices. We developed a stretchable substrate with high elasticity by forming a porous structure on polydimethylsiloxane (PDMS). To optimize the porous structure, we propose a manufacturing process that utilizes a high-pressure steam with different viscosities (400, 800, 2100, and 3000 cP) of an uncured PDMS solution. The proposed method simplifies the manufacturing of porous structures and is cost-effective compared to other technologies. Porous structures of various viscosities were formed, and their electrical and mechanical properties evaluated. Porous PDMS (3000 cP) was formed in a sponge-like three-dimensional porous structure, compared to PDMS formed by other viscosities. The elongation of porous PDMS (3000 cP) was increased by up to 30%, and the relative resistance changed to less than 1000 times with the maximum strain test. The relative resistance increased the initial resistance (R0) by approximately 10 times during the 1500-times repeated cycling tests with 30% strain. As a result, patch-type wearable devices based on soft materials can provide an innovative platform that can connect with the human skin for robotics applications and for continuous health monitoring.

Wearable Biosensors: An Alternative and Practical Approach in Healthcare and Disease Monitoring.

With the increasing prevalence of growing population, aging and chronic diseases continuously rising healthcare costs, the healthcare system is undergoing a vital transformation from the traditional hospital-centered system to an individual-centered system. Since the 20th century, wearable sensors are becoming widespread in healthcare and biomedical monitoring systems, empowering continuous measurement of critical biomarkers for monitoring of the diseased condition and health, medical diagnostics and evaluation in biological fluids like saliva, blood, and sweat. Over the past few decades, the developments have been focused on electrochemical and optical biosensors, along with advances with the non-invasive monitoring of biomarkers, bacteria and hormones, etc. Wearable devices have evolved gradually with a mix of multiplexed biosensing, microfluidic sampling and transport systems integrated with flexible materials and body attachments for improved wearability and simplicity. These wearables hold promise and are capable of a higher understanding of the correlations between analyte concentrations within the blood or non-invasive biofluids and feedback to the patient, which is significantly important in timely diagnosis, treatment, and control of medical conditions. However, cohort validation studies and performance evaluation of wearable biosensors are needed to underpin their clinical acceptance. In the present review, we discuss the importance, features, types of wearables, challenges and applications of wearable devices for biological fluids for the prevention of diseased conditions and real-time monitoring of human health. Herein, we summarize the various wearable devices that are developed for healthcare monitoring and their future potential has been discussed in detail.

Subclinical and Device-Detected Atrial Fibrillation: Pondering the Knowledge Gap: A Scientific Statement From the American Heart Association.

The widespread use of cardiac implantable electronic devices and wearable monitors has led to the detection of subclinical atrial fibrillation in a substantial proportion of patients. There is evidence that these asymptomatic arrhythmias are associated with increased risk of stroke. Thus, detection of subclinical atrial fibrillation may offer an opportunity to reduce stroke risk by initiating anticoagulation. However, it is unknown whether long-term anticoagulation is warranted and in what populations. This scientific statement explores the existing data on the prevalence, clinical significance, and management of subclinical atrial fibrillation and identifies current gaps in knowledge and areas of controversy and consensus.

Big data collision: the internet of things, wearable devices and genomics in the study of neurological traits and disease.

Advances in information technology (IT) hardware in the last decade have led to the advent of small connected devices broadly referred to as the Internet of Things (IoT). The IoT and its subcategory of wearable devices (wearables) both have the potential to greatly impact biomedical research. This focused review covers recent biomedical research using the IoT and wearables in the area of neurological traits and disease. In addition, a look into the future of biomedical research using IoT devices and wearables as well as some areas requiring further consideration by the field will be discussed.

Advances in Rational Design and Materials of High-Performance Stretchable Electromechanical Sensors.

Stretchable and wearable sensor technology has attracted significant interests and created high technological impact on portable healthcare and smart human-machine interfaces. Wearable electromechanical systems are an important part of this technology that has recently witnessed tremendous progress toward high-performance devices for commercialization. Over the past few years, great attention has been paid to simultaneously enhance the sensitivity and stretchability of the electromechanical sensors toward high sensitivity, ultra-stretchability, low power consumption or self-power functionalities, miniaturisation as well as simplicity in design and fabrication. This work presents state-of-the-art advanced materials and rational designs of electromechanical sensors for wearable applications. Advances in various sensing concepts and structural designs for intrinsic stretchable conductive materials as well as advanced rational platforms are discussed. In addition, the practical applications and challenges in the development of stretchable electromechanical sensors are briefly mentioned and highlighted.

The wrist is not the brain: Estimation of sleep by clinical and consumer wearable actigraphy devices is impacted by multiple patient- and device-specific factors.

Clinical actigraphy devices provide adequate estimates of some sleep measures across large groups. In practice, providers are asked to apply clinical or consumer wearable data to individual patient assessments. Inter-individual variability in device performance will impact such patient-specific interpretation. We assessed two devices, clinical and consumer, to determine the magnitude and predictors of this individual-level variability. One hundred and two patients (55 [53.9%] female; 56.4 [±16.3] years old) undergoing polysomnography wore Jawbone UP3 and/or Actiwatch2. Device total sleep time, sleep efficiency, wake after sleep onset and sleep latency were compared with polysomnography. Demographics, sleep architecture and clinical measures were compared to device performance. Actiwatch overestimated total sleep time by 27.2 min (95% confidence limits [CL], 138.3 min over to 84.0 under), overestimated sleep efficiency by 6.8% (95% CL, 34.1% over to 20.5% under), overestimated sleep onset latency by 2.6 min (95% CL, 63.3 over to 58.2 under) and underestimated wake after sleep onset by 50.7 min (95% CL, 162.5 under to 61.2 over). Jawbone overestimated total sleep time by 59.1 min (95% CL, 208.6 min over to 90.5 under) and overestimated sleep efficiency by 14.9% (95% CL, 52.6% over to 22.7% under). In multivariate models, age, sleep onset latency, wake after sleep onset, % N1 and apnea-hypopnea index explained only some of the variance in device performance. Gender also affected performance. Actiwatch and Jawbone mis-estimate sleep measures with very wide confidence limits and accuracy varies with multiple patient-level characteristics. Given these large individual inaccuracies, data from these devices must be applied only with extreme caution in clinical practice.

Needs for aids and equipment for the management of epilepsy in an Australian cohort.

AIM: This paper investigated the bases of needs for a range of epilepsy aids and equipment and expressed concerns about the use of such devices. METHOD: There was a 29.6% response rate (n = 393 of 1328) to Wave 4 of the Australian Epilepsy Longitudinal Study (AELS). The focus of Wave 4 was on the expressed needs and affordability of aids and equipment for people with epilepsy (PWE) and quality of life (QoL). Quantitative analysis was used to examine the association between self-reported need for aids and equipment, sociodemographic information, and QoL. Open-ended responses were subject to qualitative analysis. RESULTS: Approximately one-fifth of the sample felt that they needed specific aids, including emergency ID bracelets, seizure alarms, and seizure monitors. Those respondents who felt that they needed aids had more frequent seizures, had been recently injured by a seizure, and were less prosperous. The QoL of those in need of equipment was lower than that of those who felt that they did not need it. Qualitative analysis revealed a need for more information about the aids available, issues associated with affordability, and some concern about the utility of these aids for those who lived alone. DISCUSSION: Much research to date has focussed on the development and validation of devices for PWE and standards for testing. Fewer studies deal with the needs and experiences of PWE with regard to the use of such equipment. The development of these devices needs to ensure patient comfort and acceptability. In addition, there is a need to canvas the views of family, caregivers, and primary care providers on the usability of epilepsy aids and equipment. CONCLUSION: Further person-centered research is needed in assessing the need for and usability of aids and equipment for the management of epilepsy.

Seizure detection devices and health-related quality of life: A patient- and caregiver-centered evaluation.

INTRODUCTION: The unpredictability of epilepsy has a severe impact on health-related quality of life (HR-QOL) for people with epilepsy. Seizure detection devices have the potential to improve HR-QOL by improving seizure safety, reducing caregiver hypervigilance, and reducing seizure anxiety. Emerging data have led to an improved understanding of characteristics that promote acceptability of detection devices for people with epilepsy and caregivers. However, whether usage of seizure detection devices is associated with clinically meaningful improvement in anxiety and HR-QOL remains poorly understood. METHODS: We analyzed cross-sectional survey data collected first-hand from 371 people with epilepsy and caregivers on seizure detection device and HR-QOL using an enriched population of electronic seizure diary users. Metrics related to quality of life and anxiety reduction were compared between users and nonusers of seizure detection devices. RESULTS: Compared with nonusers of seizure detection devices, device users were significantly more likely to have been impacted by epilepsy in multiple HR-QOL domains, including anxiety, mood, emotional regulation/aggression, speech/language, sleep quality, social life, activities of daily living, independence, and education/academic potential. The majority (80.2%) of people using seizure detection devices experienced moderate or greater anxiety reduction from seizure detection device usage, while 11.1% reported that detection devices did not help at all with anxiety. Despite potential benefit, seizure detection devices were used only by a minority (21.8%) of people with epilepsy surveyed, and usage tended to be skewed toward younger patient age, higher income, and caregivers. There was no significant difference in overall HR-QOL between users and nonusers. CONCLUSIONS: Seizure detection devices provide moderate or greater anxiety reduction among the majority of people with epilepsy and their caregivers, but current translatability into improvements in overall HR-QOL may be limited. Affordability and technological support are potential barriers to maximizing benefit equally among the epilepsy community. These considerations may be useful to help guide future device development and inform patient-clinician discussions on device usage and HR-QOL.

Telehealth in the time of Corona: 'doctor in the house'.

The COVID-19 pandemic has led to many physicians working from home whenever possible. Although the concept of 'remote' patient care has been around for decades, present circumstances have provided a grand impetus in that direction with a view to protecting both patient and caregiver. In this article, we discuss some of the various challenges to moving forward with telemedicine, drawing in part on our own experiences in dealing with the COVID-19 pandemic. Clinical, technical, financial and cultural barriers to telemedicine are identified, along with a discussion concerning anticipated benefits. We conclude that the COVID-19 pandemic will likely forever change how healthcare is conducted as telemedicine figures increasingly prominently in the clinical landscape.

Current Evidence for Continuous Vital Signs Monitoring by Wearable Wireless Devices in Hospitalized Adults: Systematic Review.

BACKGROUND: Continuous monitoring of vital signs by using wearable wireless devices may allow for timely detection of clinical deterioration in patients in general wards in comparison to detection by standard intermittent vital signs measurements. A large number of studies on many different wearable devices have been reported in recent years, but a systematic review is not yet available to date. OBJECTIVE: The aim of this study was to provide a systematic review for health care professionals regarding the current evidence about the validation, feasibility, clinical outcomes, and costs of wearable wireless devices for continuous monitoring of vital signs. METHODS: A systematic and comprehensive search was performed using PubMed/MEDLINE, EMBASE, and Cochrane Central Register of Controlled Trials from January 2009 to September 2019 for studies that evaluated wearable wireless devices for continuous monitoring of vital signs in adults. Outcomes were structured by validation, feasibility, clinical outcomes, and costs. Risk of bias was determined by using the Mixed Methods Appraisal Tool, quality assessment of diagnostic accuracy studies 2nd edition, or quality of health economic studies tool. RESULTS: In this review, 27 studies evaluating 13 different wearable wireless devices were included. These studies predominantly evaluated the validation or the feasibility outcomes of these devices. Only a few studies reported the clinical outcomes with these devices and they did not report a significantly better clinical outcome than the standard tools used for measuring vital signs. Cost outcomes were not reported in any study. The quality of the included studies was predominantly rated as low or moderate. CONCLUSIONS: Wearable wireless continuous monitoring devices are mostly still in the clinical validation and feasibility testing phases. To date, there are no high quality large well-controlled studies of wearable wireless devices available that show a significant clinical benefit or cost-effectiveness. Such studies are needed to help health care professionals and administrators in their decision making regarding implementation of these devices on a large scale in clinical practice or in-home monitoring.

A Multi-Static Radar Network with Ultra-Wideband Radio-Equipped Devices.

A growing number of devices, from car key fobs to mobile phones to WiFi-routers, are equipped with ultra-wideband radios. In the network formed by these devices, communicating modules often estimate the channel impulse response to employ a matched filter to decode transmitted data or to accurately time stamp incoming messages when estimating the time-of-flight for localization. This paper investigates how such measurements of the channel impulse response can be utilized to augment existing ultra-wideband communication and localization networks to a multi-static radar network. The approach is experimentally evaluated using off-the-shelf hardware and simple, distributed filtering, and shows that a tag-free human walking in the space equipped with ultra-wideband modules can be tracked in real time. This opens the door for various location-based smart home applications, ranging from smart audio and light systems to elderly monitoring and security systems.