Diagnostic Yield of Ambulatory Reflux Monitoring Systems for Evaluation of Chronic Laryngeal Symptoms.

INTRODUCTION: Among patients with chronic laryngeal symptoms, ambulatory reflux monitoring off acid suppression is recommended to evaluate for laryngopharyngeal reflux (LPR). However, reflux monitoring systems are diverse in configuration and monitoring capabilities, which present a challenge in creating a diagnostic reference standard in these patients. This study aimed to compare diagnostic yield and performance between reflux monitoring systems in patients with chronic laryngeal symptoms. METHODS: This multicenter, international study of adult patients referred for evaluation of LPR over a 5-year period (March 2018-May 2023) assessed and compared diagnostic yield of pathologic gastroesophageal reflux (GER+) on ambulatory reflux monitoring off acid suppression. RESULTS: Of 813 patients, 296 (36%) underwent prolonged wireless pH, 532 (65%) underwent 24-hour pH-impedance monitoring, and 15 (2%) underwent both tests. Overall diagnostic yield for GER+ was 36% and greater for prolonged wireless pH compared with that for 24-hour pH-impedance monitoring (50% vs 27%; P < 0.01). Among 15 patients who underwent both prolonged wireless pH and 24-h pH-impedance monitoring, concordance between systems for GER+ was 40%. The most common source of discordance was strong evidence of GER+ across multiple days on prolonged wireless pH compared with no evidence of GER+ on pH-impedance. DISCUSSION: In this multicenter international study of patients with chronic laryngeal symptoms referred for LPR evaluation, diagnostic yield of ambulatory reflux monitoring off acid suppression was 36% and rose to 50% when using wireless pH monitoring. In patients referred for chronic laryngeal symptoms, 24-hour pH-impedance monitoring may risk a low negative predictive value in patients with unproven GER+ disease.

An Apple a Day to Keep the Parkinson's Disease Doctor Away?

It is challenging to reliably assess the motor features of Parkinson's disease in real-time. This has motivated the search for new digital outcomes that can objectively and remotely measure the severity of parkinsonian motor impairments over an extended period of time. The United States Food and Drug Administration (FDA) has recently granted a 510(k) clearance to the Rune Labs Kinematics System, an ambulatory, smartwatch-based monitoring system to remotely track tremor and dyskinesias in persons with Parkinson's disease. The FDA clearance means that this new digital approach can be regarded as being safe for use in daily practice, with acceptable correlations to clinically based measures. However, the immediate implications for clinicians are limited, because it remains to be demonstrated whether the digital signals correlate well to clinically meaningful outcomes at patient level. The impact on research is also restricted for now, as more validation studies are needed before this new digital approach can be used as primary or secondary endpoint in clinical trials. ANN NEUROL 2023;93:681-685.

Ambulatory EEG-video.

Hospital based EEG recordings have been the norm to assist in the diagnosis and management of patients with unclassified events and known drug resistant epilepsy. Ambulatory EEG (AEEG) is a tool that comes to serve the needs for a portable testing that can be done at home, often with higher accessibility compared to an epilepsy monitoring unit and with lower cost. The current technology provides good quality EEG tracing and can be done with video when needed. In this review we discuss how AEEG should be performed and the preferred indications in which this test may be of utmost help. The advent of ultra-long ambulatory recording may be the future for selected patients as this technology evolves.

Prospective multicenter study of continuous tonic-clonic seizure monitoring on Apple Watch in epilepsy monitoring units and ambulatory environments.

OBJECTIVE: Evaluate the performance of a custom application developed for tonic-clonic seizure (TCS) monitoring on a consumer-wearable (Apple Watch) device. METHODS: Participants with a history of convulsive epileptic seizures were recruited for either Epilepsy Monitoring Unit (EMU) or ambulatory (AMB) monitoring; participants without epilepsy (normal controls [NC]) were also enrolled in the AMB group. Both EMU and AMB participants wore an Apple Watch with a research app that continuously recorded accelerometer and photoplethysmography (PPG) signals, and ran a fixed-and-frozen tonic-clonic seizure detection algorithm during the testing period. This algorithm had been previously developed and validated using a separate training dataset. All EMU convulsive events were validated by video-electroencephalography (video-EEG); AMB events were validated by caregiver reporting and follow-ups. Device performance was characterized and compared to prior monitoring devices through sensitivity, false alarm rate (FAR; false-alarms per 24 h), precision, and detection delay (latency). RESULTS: The EMU group had 85 participants (4,279 h, 19 TCS from 15 participants) enrolled across four EMUs; the AMB group had 21 participants (13 outpatient, 8 NC, 6,735 h, 10 TCS from 3 participants). All but one AMB participant completed the study. Device performance in the EMU group included a sensitivity of 100 % [95 % confidence interval (CI) 79-100 %]; an FAR of 0.05 [0.02, 0.08] per 24 h; a precision of 68 % [48 %, 83 %]; and a latency of 32.07 s [standard deviation (std) 10.22 s]. The AMB group had a sensitivity of 100 % [66-100 %]; an FAR of 0.13 [0.08, 0.24] per 24 h; a precision of 22 % [11 %, 37 %]; and a latency of 37.38 s [13.24 s]. Notably, a single AMB participant was responsible for 8 of 31 false alarms. The AMB FAR excluding this participant was 0.10 [0.07, 0.14] per 24 h. DISCUSSION: This study demonstrates the practicability of TCS monitoring on a popular consumer wearable (Apple Watch) in daily use for people with epilepsy. The monitoring app had a high sensitivity and a substantially lower FAR than previously reported in both EMU and AMB environments.

Diagnostic utility of prolonged ambulatory video-electroencephalography monitoring.

OBJECTIVES: Ambulatory video-electroencephalography (video-EEG) represents a low-cost, convenient and accessible alternative to inpatient video-EEG monitoring, however few studies have examined their diagnostic yield. In this large-scale retrospective study conducted in Australia, we evaluated the efficacy of prolonged ambulatory video-EEG recordings in capturing diagnostic events and resolving the referring question. METHODS: Sequential adult and paediatric ambulatory video-EEG reports from April 2020 to June 2021 were reviewed retrospectively. Data collection included patient demographics, clinical information, and details of events and EEG abnormalities. Clinical utility was assessed by examining i) time to first diagnostic event, and ii) ability to resolve the referring questions - seizure localisation, quantification, classification, and differentiation (differentiating seizures from non-epileptic events). RESULTS: Of the 600 reports analysed, 49 % captured at least one event, and 45 % captured interictal abnormalities (epileptiform or non-epileptiform). Seizures, probable psychogenic events (mostly non-convulsive), and other non-epileptic events occurred in 13 %, 23 % and 21 % of recordings respectively, with overlap. Unreported events were captured in 53 (9 %) recordings, and unreported seizures represented more than half of all seizures captured (51 %, 392/773). Nine percent of events were missing clinical, video or electrographic data. A diagnostic event occurred in 244 (41 %) recordings, of which 14 % were captured between the fifth and eighth day of recording. Reported event frequency ≥ 1/week was the only significant predictor of diagnostic event capture. In recordings with both seizures and psychogenic events, unrecognized seizures were frequent, and seizures may be missed if recording is terminated early. The referring question was resolved in 85 % of reports with at least one event, and 53 % of all reports. Specifically, this represented 46 % of reports (235/512) for differentiation of events, and 75 % of reports (27/36) for classification of seizures. CONCLUSION: Ambulatory video-EEG recordings are of high diagnostic value in capturing clinically relevant events and resolving the referring clinical questions.

Feasibility and acceptability of measuring prenatal stress in daily life using smartphone-based ecological momentary assessment and wearable physiological monitors.

High levels of stress during pregnancy can have lasting effects on maternal and offspring health, which disproportionately impacts families facing financial strain, systemic racism, and other forms of social oppression. Developing ways to monitor daily life stress during pregnancy is important for reducing stress-related health disparities. We evaluated the feasibility and acceptability of using mobile health (mHealth) technology (i.e., wearable biosensors, smartphone-based ecological momentary assessment) to measure prenatal stress in daily life. Fifty pregnant women (67% receiving public assistance; 70% Black, 6% Multiracial, 24% White) completed 10 days of ambulatory assessment, in which they answered smartphone-based surveys six times a day and wore a chest-band device (movisens EcgMove4) to monitor their heart rate, heart rate variability, and activity level. Feasibility and acceptability were evaluated using behavioral meta-data and participant feedback. Findings supported the feasibility and acceptability of mHealth methods: Participants answered approximately 75% of the surveys per day and wore the device for approximately 10 hours per day. Perceived burden was low. Notably, participants with higher reported stressors and financial strain reported lower burden associated with the protocol than participants with fewer life stressors, highlighting the feasibility of mHealth technology for monitoring prenatal stress among pregnant populations living with higher levels of contextual stressors. Findings support the use of mHealth technology to measure prenatal stress in real-world, daily life settings, which shows promise for informing scalable, technology-assisted interventions that may help to reduce health disparities by enabling more accessible and comprehensive care during pregnancy.

Automated Detection of In-Home Activities with Ultra-Wideband Sensors.

As Canada's population of older adults rises, the need for aging-in-place solutions is growing due to the declining quality of long-term-care homes and long wait times. While the current standards include questionnaire-based assessments for monitoring activities of daily living (ADLs), there is an urgent need for advanced indoor localization technologies that ensure privacy. This study explores the use of Ultra-Wideband (UWB) technology for activity recognition in a mock condo in the Glenrose Rehabilitation Hospital. UWB systems with built-in Inertial Measurement Unit (IMU) sensors were tested, using anchors set up across the condo and a tag worn by patients. We tested various UWB setups, changed the number of anchors, and varied the tag placement (on the wrist or chest). Wrist-worn tags consistently outperformed chest-worn tags, and the nine-anchor configuration yielded the highest accuracy. Machine learning models were developed to classify activities based on UWB and IMU data. Models that included positional data significantly outperformed those that did not. The Random Forest model with a 4 s data window achieved an accuracy of 94%, compared to 79.2% when positional data were excluded. These findings demonstrate that incorporating positional data with IMU sensors is a promising method for effective remote patient monitoring.

A Lifestyle Monitoring System for Older Adults Living Independently Using Low-Resolution Smart Meter Data.

BACKGROUND: Monitoring the lifestyles of older adults helps promote independent living and ensure their well-being. The common technologies for home monitoring include wearables, ambient sensors, and smart household meters. While wearables can be intrusive, ambient sensors require extra installation, and smart meters are becoming integral to smart city infrastructure. Research Gap: The previous studies primarily utilized high-resolution smart meter data by applying Non-Intrusive Appliance Load Monitoring (NIALM) techniques, leading to significant privacy concerns. Meanwhile, some Japanese power companies have successfully employed low-resolution data to monitor lifestyle patterns discreetly. SCOPE AND METHODOLOGY: This study develops a lifestyle monitoring system for older adults using low-resolution smart meter data, mapping electricity consumption to appliance usage. The power consumption data are collected at 15-min intervals, and the background power threshold distinguishes between the active and inactive periods (0/1). The system quantifies activity through an active score and assesses daily routines by comparing these scores against the long-term norms. Key Outcomes/Contributions: The findings reveal that low-resolution data can effectively monitor lifestyle patterns without compromising privacy. The active scores and regularity assessments calculated using correlation coefficients offer a comprehensive view of residents' daily activities and any deviations from the established patterns. This study contributes to the literature by validating the efficacy of low-resolution data in lifestyle monitoring systems and underscores the potential of smart meters in enhancing elderly people's care.

Current Knowledge about ActiGraph GT9X Link Activity Monitor Accuracy and Validity in Measuring Steps and Energy Expenditure: A Systematic Review.

Over recent decades, wearable inertial sensors have become popular means to quantify physical activity and mobility. However, research assessing measurement accuracy and precision is required, especially before using device-based measures as outcomes in trials. The GT9X Link is a recent activity monitor available from ActiGraph, recognized as a "gold standard" and previously used as a criterion measure to assess the validity of various consumer-based activity monitors. However, the validity of the ActiGraph GT9X Link is not fully elucidated. A systematic review was undertaken to synthesize the current evidence for the criterion validity of the ActiGraph GT9X Link in measuring steps and energy expenditure. This review followed the PRISMA guidelines and eight studies were included with a combined sample size of 558 participants. We found that (1) the ActiGraph GT9X Link generally underestimates steps; (2) the validity and accuracy of the device in measuring steps seem to be influenced by gait speed, device placement, filtering process, and monitoring conditions; and (3) there is a lack of evidence regarding the accuracy of step counting in free-living conditions and regarding energy expenditure estimation. Given the limited number of included studies and their heterogeneity, the present review emphasizes the need for further validation studies of the ActiGraph GT9X Link in various populations and in both controlled and free-living settings.

Apple Watch 6 vs. Galaxy Watch 4: A Validity Study of Step-Count Estimation in Daily Activities.

The purpose of this study was to examine the validity of two wearable smartwatches (the Apple Watch 6 (AW) and the Galaxy Watch 4 (GW)) and smartphone applications (Apple Health for iPhone mobiles and Samsung Health for Android mobiles) for estimating step counts in daily life. A total of 104 healthy adults (36 AW, 25 GW, and 43 smartphone application users) were engaged in daily activities for 24 h while wearing an ActivPAL accelerometer on the thigh and a smartwatch on the wrist. The validities of the smartwatch and smartphone estimates of step counts were evaluated relative to criterion values obtained from an ActivPAL accelerometer. The strongest relationship between the ActivPAL accelerometer and the devices was found for the AW (r = 0.99, p < 0.001), followed by the GW (r = 0.82, p < 0.001), and the smartphone applications (r = 0.93, p < 0.001). For overall group comparisons, the MAPE (Mean Absolute Percentage Error) values (computed as the average absolute value of the group-level errors) were 6.4%, 10.5%, and 29.6% for the AW, GW, and smartphone applications, respectively. The results of the present study indicate that the AW and GW showed strong validity in measuring steps, while the smartphone applications did not provide reliable step counts in free-living conditions.

Recent Innovations in Footwear and the Role of Smart Footwear in Healthcare-A Survey.

Smart shoes have ushered in a new era of personalised health monitoring and assistive technologies. Smart shoes leverage technologies such as Bluetooth for data collection and wireless transmission, and incorporate features such as GPS tracking, obstacle detection, and fitness tracking. As the 2010s unfolded, the smart shoe landscape diversified and advanced rapidly, driven by sensor technology enhancements and smartphones' ubiquity. Shoes have begun incorporating accelerometers, gyroscopes, and pressure sensors, significantly improving the accuracy of data collection and enabling functionalities such as gait analysis. The healthcare sector has recognised the potential of smart shoes, leading to innovations such as shoes designed to monitor diabetic foot ulcers, track rehabilitation progress, and detect falls among older people, thus expanding their application beyond fitness into medical monitoring. This article provides an overview of the current state of smart shoe technology, highlighting the integration of advanced sensors for health monitoring, energy harvesting, assistive features for the visually impaired, and deep learning for data analysis. This study discusses the potential of smart footwear in medical applications, particularly for patients with diabetes, and the ongoing research in this field. Current footwear challenges are also discussed, including complex construction, poor fit, comfort, and high cost.

Wearable-Based Integrated System for In-Home Monitoring and Analysis of Nocturnal Enuresis.

Nocturnal enuresis (NE) is involuntary bedwetting during sleep, typically appearing in young children. Despite the potential benefits of the long-term home monitoring of NE patients for research and treatment enhancement, this area remains underexplored. To address this, we propose NEcare, an in-home monitoring system that utilizes wearable devices and machine learning techniques. NEcare collects sensor data from an electrocardiogram, body impedance (BI), a three-axis accelerometer, and a three-axis gyroscope to examine bladder volume (BV), heart rate (HR), and periodic limb movements in sleep (PLMS). Additionally, it analyzes the collected NE patient data and supports NE moment estimation using heuristic rules and deep learning techniques. To demonstrate the feasibility of in-home monitoring for NE patients using our wearable system, we used our datasets from 30 in-hospital patients and 4 in-home patients. The results show that NEcare captures expected trends associated with NE occurrences, including BV increase, HR increase, and PLMS appearance. In addition, we studied the machine learning-based NE moment estimation, which could help relieve the burdens of NE patients and their families. Finally, we address the limitations and outline future research directions for the development of wearable systems for NE patients.

[Analysis of the Current Application Status for Clinical and Home Monitoring of Obstructive Sleep Apnea-Hypopnea Syndrome].

The study provides an overview of the development status of sleep disorder monitoring devices. Currently, polysomnography (PSG) is the gold standard for diagnosing sleep disorders, necessitating multiple leads and requiring overnight monitoring in a sleep laboratory, which can be cumbersome for patients. Nevertheless, the performance of PSG has been enhanced through research on sleep disorder monitoring and sleep staging optimization. An alternative device is the home sleep apnea testing (HSAT), which enables patients to monitor their sleep at home. However, HSAT does not attain the same level of accuracy in sleep staging as PSG, rendering it inappropriate for screening individuals with asymptomatic or mild obstructive sleep apnea-hypopnea syndrome (OSAHS). The study suggests that establishing a Chinese sleep staging database and developing home sleep disorder monitoring devices that can serve as alternatives to PSG will represent a future development direction.

Detection of subclinical epileptiform discharges in Alzheimer's disease using long-term outpatient EEG monitoring.

BACKGROUND: In patients with Alzheimer's disease (AD) without clinical seizures, up to half have epileptiform discharges on long-term in-patient electroencephalography (EEG) recordings. Long-term in-patient monitoring is obtrusive, and expensive as compared to outpatient monitoring. No studies have so far investigated if long-term outpatient EEG monitoring is able to identify epileptiform discharges in AD. Our aim is to investigate if epileptiform discharges as measured with ear-EEG are more common in patients with AD compared to healthy elderly controls (HC). METHODS: In this longitudinal observational study, 24 patients with mild to moderate AD and 15 age-matched HC were included in the analysis. Patients with AD underwent up to three ear-EEG recordings, each lasting up to two days, within 6 months. RESULTS: The first recording was defined as the baseline recording. At baseline, epileptiform discharges were detected in 75.0% of patients with AD and in 46.7% of HC (p-value = 0.073). The spike frequency (spikes or sharp waves/24 h) was significantly higher in patients with AD as compared to HC with a risk ratio of 2.90 (CI: 1.77-5.01, p < 0.001). Most patients with AD (91.7%) showed epileptiform discharges when combining all ear-EEG recordings. CONCLUSIONS: Long-term ear-EEG monitoring detects epileptiform discharges in most patients with AD with a three-fold increased spike frequency compared to HC, which most likely originates from the temporal lobes. Since most patients showed epileptiform discharges with multiple recordings, elevated spike frequency should be considered a marker of hyperexcitability in AD.

Sustained Reduction in Pulmonary Artery Pressures and Hospitalizations During 2 Years of Ambulatory Monitoring.

BACKGROUND: Therapy guided by pulmonary artery (PA) pressure monitoring reduces PA pressures and heart failure hospitalizations (HFH) during the first year, but the durability of efficacy and safety through 2 years is not known. METHODS AND RESULTS: The CardioMEMS Post-Approval Study investigated whether benefit and safety were generalized and sustained. Enrollment at 104 centers in the United States included 1200 patients with NYHA Class III symptoms on recommended HF therapies with prior HFH. Therapy was adjusted toward PA diastolic pressure 8-20 mmHg. Intervention frequency and PA pressure reduction were most intense during first 90 days, with sustained reduction of PA diastolic pressure from baseline 24.7 mmHg to 21.0 at 1 year and 20.8 at 2 years for all patients. Patients completing two year follow-up (n = 710) showed similar 2-year reduction (23.9 to 20.8 mmHg), with reduction in PA mean pressure (33.7 to 29.4 mmHg) in patients with reduced left ventricular ejection. The HFH rate was 1.25 events/patient/year prior to sensor implant, 0.54 at 1 year, and 0.37 at 2 years, with 59% of patients free of HFH during follow-up. CONCLUSIONS: Reduction in PA pressures and hospitalizations were early and sustained during 2 years of PA pressure-guided management, with no signal of safety concerns regarding the implanted sensor.

Translating Pressure Into Practice: Operational Characteristics of Ambulatory Hemodynamic Monitoring Program in the United States.

BACKGROUND: Ambulatory hemodynamic monitoring (AHM) using an implantable pulmonary artery pressure sensor (CardioMEMS) is effective in improving outcomes for patients with heart failure. The operations of AHM programs are crucial to clinical efficacy of AHM yet have not been described. METHODS AND RESULTS: An anonymous, voluntary, web-based survey was developed and emailed to clinicians at AHM centers in the United States. Survey questions were related to program volume, staffing, monitoring practices, and patient selection criteria. Fifty-four respondents (40%) completed the survey. Respondents were 44% (n = 24) advanced HF cardiologists and 30% (n = 16) advanced nurse practitioners. Most respondents practice at a center that implants left ventricular assist devices (70%) or performs heart transplantation (54%). Advanced practice providers provide day-to-day monitoring and management in most programs (78%), and use of protocol-driven care is limited (28%). Perceived patient nonadherence and inadequate insurance coverage are cited as the primary barriers to AHM. CONCLUSIONS: Despite broad US Food and Drug Administration approval for patients with symptoms and at increased risk for worsening heart failure, the adoption of pulmonary artery pressure monitoring is concentrated at advanced heart failure centers, and modest numbers of patients are implanted at most centers. Understanding and addressing the barriers to referral of eligible patients and to broader adoption in community heart failure programs is needed to maximize the clinical benefits of AHM.

How often do healthy people cough?

Objective cough frequency has been reported in several respiratory conditions but the amount that healthy individuals cough daily is unclear. Seventy-nine healthy volunteers (38 males, median [IQR] age 41y [IQR 30-53]) completed 24-hour ambulatory cough monitoring (VitaloJAK™). The audio recording was filtered using a custom written algorithm to remove non-cough sounds and then all individual explosive cough sounds in the filtered file were tagged electronically by trained cough counters. Most coughing occurred during the day and cough numbers over 24 h were generally low (geometric mean of 4.6 coughs) but there was large variability; ranging from 0 to 136 coughs overall. Cough frequency was independent of participant characteristics apart from sex with males coughing significantly, 4-5 fold, more than females during the day and over 24 h (median [IQR] 16.1 [3.8-33.4] vs. 4.1 [1.0-15.0] total coughs; p = 0.015). This is the first report to describe cough frequency in a balanced group of healthy adults using an accurate cough monitoring system. The data reveal a further example of sexual dimorphism in cough, which warrants additional investigation.

Acceptability and Adherence to Home, Kiosk, and Clinic Blood Pressure Measurement Compared to 24-H Ambulatory Monitoring.

BACKGROUND: The US Preventive Services Task Force recommends measuring blood pressure (BP) outside of clinic/office settings. While various options are available, including home devices, BP kiosks, and 24-h ambulatory BP monitoring (ABPM), understanding patient acceptability and adherence is a critical factor for implementation. OBJECTIVE: To compare the acceptability and adherence of clinic, home, kiosk, and ABPM measurement. DESIGN: Comparative diagnostic accuracy study which randomized adults to one of three BP measurement arms: clinic, home, and kiosk. ABPM was conducted on all participants. PARTICIPANTS: Adults (18-85 years) receiving care at 12 Kaiser Permanente Washington primary care clinics (Washington State, USA) with a high BP (≥ 138 mmHg systolic or ≥ 88 mmHg diastolic) in the electronic health record with no hypertension diagnosis and on no hypertensive medications and with high BP at a research screening visit. MEASURES: Patient acceptability was measured using a validated survey which was used to calculate an overall acceptability score (range 1-7) at baseline, after completing their assigned BP measurement intervention, and after completing ABPM. Adherence was defined based on the pre-specified number of BP measurements completed. KEY RESULTS: Five hundred ten participants were randomized (mean age 59 years), with mean BP of 150/88. Overall acceptability score was highest (i.e. most acceptable) for Home BP (mean 6.2, SD 0.7) and lowest (least acceptable) for ABPM (mean 5.0, SD 1.0); scores were intermediate for Clinic (5.5, SD 1.1) and Kiosk (5.4, SD 1.0). Adherence was higher for Home (154/170, 90.6%) and Clinic (150/172, 87.2%) than for Kiosk (114/168, 67.9%)). The majority of participants (467/510, 91.6%) were adherent to ABPM. CONCLUSIONS: Participants found home BP measurement most acceptable followed by clinic, BP kiosks, and ABPM. Our findings, coupled with recent evidence regarding the accuracy of home BP measurement, further support the routine use of home-based BP measurement in primary care practice in the US. TRIAL REGISTRATION: ClinicalTrials.gov NCT03130257 https://clinicaltrials.gov/ct2/show/NCT03130257.

Seizure occurrence is linked to multiday cycles in diverse physiological signals.

OBJECTIVE: The factors that influence seizure timing are poorly understood, and seizure unpredictability remains a major cause of disability. Work in chronobiology has shown that cyclical physiological phenomena are ubiquitous, with daily and multiday cycles evident in immune, endocrine, metabolic, neurological, and cardiovascular function. Additionally, work with chronic brain recordings has identified that seizure risk is linked to daily and multiday cycles in brain activity. Here, we provide the first characterization of the relationships between the cyclical modulation of a diverse set of physiological signals, brain activity, and seizure timing. METHODS: In this cohort study, 14 subjects underwent chronic ambulatory monitoring with a multimodal wrist-worn sensor (recording heart rate, accelerometry, electrodermal activity, and temperature) and an implanted responsive neurostimulation system (recording interictal epileptiform abnormalities and electrographic seizures). Wavelet and filter-Hilbert spectral analyses characterized circadian and multiday cycles in brain and wearable recordings. Circular statistics assessed electrographic seizure timing and cycles in physiology. RESULTS: Ten subjects met inclusion criteria. The mean recording duration was 232 days. Seven subjects had reliable electroencephalographic seizure detections (mean = 76 seizures). Multiday cycles were present in all wearable device signals across all subjects. Seizure timing was phase locked to multiday cycles in five (temperature), four (heart rate, phasic electrodermal activity), and three (accelerometry, heart rate variability, tonic electrodermal activity) subjects. Notably, after regression of behavioral covariates from heart rate, six of seven subjects had seizure phase locking to the residual heart rate signal. SIGNIFICANCE: Seizure timing is associated with daily and multiday cycles in multiple physiological processes. Chronic multimodal wearable device recordings can situate rare paroxysmal events, like seizures, within a broader chronobiology context of the individual. Wearable devices may advance the understanding of factors that influence seizure risk and enable personalized time-varying approaches to epilepsy care.

Home nocturnal infrared video to record non-rapid eye movement sleep parasomnias.

To assess the feasibility, the acceptability and the usefulness of home nocturnal infrared video in recording the frequency and the complexity of non-rapid eye movement sleep parasomnias in adults, and in monitoring the treatment response. Twenty adult patients (10 males, median age 27.5 years) with a diagnosis of non-rapid eye movement parasomnia were consecutively enrolled. They had a face-to-face interview, completed self-reported questionnaires to assess clinical characteristics and performed a video-polysomnography in the Sleep Unit. Patients were then monitored at home during at least five consecutive nights using infrared-triggered cameras. They completed a sleep diary and questionnaires to evaluate the number of parasomniac episodes at home and the acceptability of the home nocturnal infrared video recording. Behavioural analyses were performed on home nocturnal infrared video and video-polysomnography recordings. Eight patients treated by clonazepam underwent a second home nocturnal infrared video recording during five consecutive days. All patients had at least one parasomniac episode during the home nocturnal infrared video monitoring, compared with 75% during the video-polysomnography. A minimum of three consecutive nights with home nocturnal infrared video was required to record at least one parasomniac episode. Most patients underestimated the frequency of episodes on the sleep diary compared with home nocturnal infrared video. Episodes recorded at home were often more complex than those recorded during the video-polysomnography. The user-perceived acceptability of the home nocturnal infrared video assessment was excellent. The frequency and the complexity of the parasomniac episodes decreased with clonazepam. Home nocturnal infrared video has good feasibility and acceptability, and may improve the evaluation of the phenotype and severity of the non-rapid eye movement parasomnias and of the treatment response in an ecological setting.