scholarly journals Deconstructing Commercial Wearable Technology: Contributions toward Accurate and Free-Living Monitoring of Sleep

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5071
Author(s):  
Lauren E. Rentz ◽  
Hana K. Ulman ◽  
Scott M. Galster
Keyword(s):  
Sleep Stage ◽  
Third Party ◽  
Physiological Signals ◽  
Device Performance ◽  
Contributing Factors ◽  
Sleep State ◽  
Free Living ◽  
Regulatory Oversight ◽  
Manufactured Products ◽  
Sleep Assessment

Despite prolific demands and sales, commercial sleep assessment is primarily limited by the inability to “measure” sleep itself; rather, secondary physiological signals are captured, combined, and subsequently classified as sleep or a specific sleep state. Using markedly different approaches compared with gold-standard polysomnography, wearable companies purporting to measure sleep have rapidly developed during recent decades. These devices are advertised to monitor sleep via sensors such as accelerometers, electrocardiography, photoplethysmography, and temperature, alone or in combination, to estimate sleep stage based upon physiological patterns. However, without regulatory oversight, this market has historically manufactured products of poor accuracy, and rarely with third-party validation. Specifically, these devices vary in their capacities to capture a signal of interest, process the signal, perform physiological calculations, and ultimately classify a state (sleep vs. wake) or sleep stage during a given time domain. Device performance depends largely on success in all the aforementioned requirements. Thus, this review provides context surrounding the complex hardware and software developed by wearable device companies in their attempts to estimate sleep-related phenomena, and outlines considerations and contributing factors for overall device success.

scholarly journals Performance of Seven Consumer Sleep-Tracking Devices Compared with Polysomnography

SLEEP ◽  
2020 ◽  
Author(s):  
Evan D Chinoy ◽  
Joseph A Cuellar ◽  
Kirbie E Huwa ◽  
Jason T Jameson ◽  
Catherine H Watson ◽  
...  
Keyword(s):  
Performance Measures ◽  
Gold Standard ◽  
High Performance ◽  
Sleep Stage ◽  
Sleep Laboratory ◽  
Sleep Assessment ◽  
Sleep Condition ◽  
Different Populations ◽  
Tracking Devices ◽  
Better Than

Abstract Study Objectives Consumer sleep-tracking devices are widely used and becoming more technologically advanced, creating strong interest from researchers and clinicians for their possible use as alternatives to standard actigraphy. We therefore tested the performance of many of the latest consumer sleep-tracking devices, alongside actigraphy, versus the gold-standard sleep assessment technique, polysomnography (PSG). Methods In total, 34 healthy young adults (22 women; 28.1 ± 3.9 years, mean ± SD) were tested on three consecutive nights (including a disrupted sleep condition) in a sleep laboratory with PSG, along with actigraphy (Philips Respironics Actiwatch 2) and a subset of consumer sleep-tracking devices. Altogether, four wearable (Fatigue Science Readiband, Fitbit Alta HR, Garmin Fenix 5S, Garmin Vivosmart 3) and three non-wearable (EarlySense Live, ResMed S+, SleepScore Max) devices were tested. Sleep/wake summary and epoch-by-epoch agreement measures were compared with PSG. Results Most devices (Fatigue Science Readiband, Fitbit Alta HR, EarlySense Live, ResMed S+, SleepScore Max) performed as well as or better than actigraphy on sleep/wake performance measures, while the Garmin devices performed worse. Overall, epoch-by-epoch sensitivity was high (all ≥0.93), specificity was low-to-medium (0.18-0.54), sleep stage comparisons were mixed, and devices tended to perform worse on nights with poorer/disrupted sleep. Conclusions Consumer sleep-tracking devices exhibited high performance in detecting sleep, and most performed equivalent to (or better than) actigraphy in detecting wake. Device sleep stage assessments were inconsistent. Findings indicate that many newer sleep-tracking devices demonstrate promising performance for tracking sleep and wake. Devices should be tested in different populations and settings to further examine their wider validity and utility.

Biological Rhythm Based Wearable Sleep State Observer

2007 ◽  
Vol 11 (2) ◽  
pp. 232-241 ◽  
Author(s):  
Yuki Wakuda ◽  
◽  
Akiko Noda ◽  
Yasuhisa Hasegawa ◽  
Fumihito Arai ◽  
...  
Keyword(s):  
Sleep Stage ◽  
Biological Rhythm ◽  
Sleep Cycle ◽  
Stress System ◽  
Sleep State ◽  
Human Sleep ◽  
Sensor Device ◽  
Preset Time ◽  
Pulse Waves ◽  
Life Cycle Pattern

This research aimed to observe human biological rhythm and adjust the human sleep wake pattern based on controlling wakeup timing using low stress system. An ordinary alarm clock operates according to preset time. Biological rhythm determines the human sleep cycle, which affects sleep depth and wakeup timing, which in turn resets the daily rhythm that affects human’s behavior, life-cycle pattern, life-style related disease. We developed a wearable biological rhythm based awakening controller (BRAC) that determines the biological rhythm in the sleep state (sleep cycle) and stimulates the user at a suitable time to enable the person to wakeup refreshed. The proposed system BRAC gauges human’s sleep quality and rhythms from peak to peak interval time of fingertip-pulse waves, that are measured more easily than polysomnography (PSG). In this paper, we detail the method of sleep cycle estimation using a wearable sensor device as the first feature of BRAC, then, in experiments, evaluate the performance of sleep cycle estimation based on a comparison of the BRAC-sleep cycle and the PSG-determined sleep stage.

scholarly journals Sleep Disorders in Patients with Psoriatic Arthritis

2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Mariana Castanho Risso
Keyword(s):  
Metabolic Syndrome ◽  
Psoriatic Arthritis ◽  
Sleep Disorders ◽  
Sleep Disturbances ◽  
Public Health Issue ◽  
Berlin Questionnaire ◽  
Sleep State ◽  
Simultaneous Control ◽  
Sleep Assessment

Sleep disorders are currently a major public health issue in Brazil, due to its high incidence and difficult diagnosis, identification of type and treatment.1 Rheumatic disorders have been associated with changes in sleep state, which cause reduction in quality of life, eventually reduced by the chronic inflammatory process of the primary disease.2–6 This study aimed to identify and describe the existence of sleep disturbances in patients with psoriatic arthritis, as well as to verify possible association of sleep disorders with metabolic syndrome and other parameters in these individuals. Thirty one patients with psoriatic arthritis from a Rheumatology Outpatient Clinic were analyzed. Three sleep assessment questionnaires were employed: Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (EPW) and The Berlin Questionnaire (BQ). Sleep walking or talking were also inquired as a complementary scale. Sociodemographic variables and the presence of hypertension, obesity, diabetes, dyslipidemia and metabolic syndrome have also been investigated. On average, sleep disorders were found in 54.83% of the studied patients (64.5% from PSQI, 51.6% from EPW and 48.4% from Berlin) and around 70% of sleep disorders in patients with simultaneous diagnosis of metabolic syndrome and psoriatic arthritis. From these results, it is notable that sleep disorders are common in patients diagnosed with psoriatic arthritis. Thus, this pathology demands greater attention in clinical practice and search for ideal and complete therapy, in addition to simultaneous control of arthritis, sleep, hypertension, dyslipidemia and obesity.

Change in recruitment order of motor units in human parasternal intercostal muscles with sleep state

1993 ◽  
Vol 74 (6) ◽  
pp. 2718-2723 ◽  
Author(s):  
W. A. Whitelaw ◽  
K. P. Rimmer ◽  
H. S. Sun
Keyword(s):  
Sleep Stage ◽  
Human Subjects ◽  
Motor Units ◽  
Excitatory Input ◽  
Sleep State ◽  
Intercostal Muscles ◽  
Intramuscular Electrodes ◽  
Normal Human ◽  
Low Threshold ◽  
Recruitment Order

Recruitment order of individual motor units in the early part of inspiration in parasternal intercostal muscles was observed in normal human subjects during wakefulness and non-rapid-eye-movement sleep. Electromyograms from bipolar fine wire intramuscular electrodes were recorded while the subjects lay supine in a sleep laboratory, and sleep stage was determined by polysomnography. From wakefulness to sleep there were numerous examples of shifts in order of recruitment among the low threshold units of early inspiration. There were corresponding shifts in the order of derecruitment of these units. Analysis of frequency of firing of units also suggested that the levels of excitatory input to one unit of a pair could be altered relative to the level of input of the other one. The data imply that there are at least minor differences in distribution of excitatory inputs from various sources among motoneurons of this muscle pool.

scholarly journals A review of automated sleep stage scoring based on physiological signals for the new millennia

2019 ◽  
Vol 176 ◽  
pp. 81-91 ◽  
Author(s):  
Oliver Faust ◽  
Hajar Razaghi ◽  
Ragab Barika ◽  
Edward J Ciaccio ◽  
U Rajendra Acharya
Keyword(s):  
Sleep Stage ◽  
Physiological Signals ◽  
Sleep Stage Scoring

scholarly journals Cardiovascular responses to nonrespiratory and respiratory arousals in a porcine model

2001 ◽  
Vol 90 (1) ◽  
pp. 114-120 ◽  
Author(s):  
Sandrine H. Launois ◽  
Nathan Averill ◽  
Joseph H. Abraham ◽  
Debra A. Kirby ◽  
J. Woodrow Weiss
Keyword(s):  
Porcine Model ◽  
Sleep Stage ◽  
Cardiovascular Responses ◽  
Hemodynamic Response ◽  
Rapid Eye Movement Sleep ◽  
Sleep State ◽  
Renal Vasoconstriction ◽  
Airway Occlusion ◽  
Arterial Blood ◽  
Renal Vascular

Spontaneous and provoked nonrespiratory arousals can be accompanied by a patterned hemodynamic response. To investigate whether a patterned response is also elicited by respiratory arousals, we compared nonrespiratory arousals (NRA) to respiratory arousals (RA) induced by airway occlusion during non-rapid eye movement sleep. We monitored mean arterial blood pressure (MAP), heart rate, iliac and renal blood flow, and sleep stage in 7 pigs during natural sleep. Iliac and renal vascular resistance were calculated. Airway occlusions were obtained by manually inflating a chronically implanted tracheal balloon during sleep. The balloon was quickly deflated as soon as electroencephalogram arousal occurred. As previously reported, NRA generally elicited iliac vasodilation, renal vasoconstriction, little change in MAP, and tachycardia. In contrast, RA generally elicited iliac and renal vasoconstriction, an increase in MAP and tachycardia. The frequent occurrence of iliac vasoconstriction and arterial pressure elevation following RA but not NRA suggests that sleep state change alone does not account for the hemodynamic response to airway occlusion during sleep.

scholarly journals Medical students’ technology use for learning: Contributing factors and self-regulation

2021 ◽  
Author(s):  
Binbin Zheng
Keyword(s):  
Medical Students ◽  
Learning Strategies ◽  
Technology Use ◽  
Flipped Classroom ◽  
Self Regulation ◽  
Structured Interview ◽  
Perceived Usefulness ◽  
Qualitative Description ◽  
Third Party ◽  
Contributing Factors

Abstract Background: With medical education shifting towards student-centered models, medical students are expected to be self-regulated learners. Advancement in technologies has been suggested to be supportive of students’ self-regulated learning (SRL). There is an urgent need to understand what factors contributed to students’ self-initiated technology use, and how does students’ technology use influence their SRL. Method: This study took place in a midwestern university medical school, which implements a flipped classroom model where students are required to learn independently all the course materials before class. Twenty-six first- and second-year medical students participated in a semi-structured interview about their self-initiated technology use, contributing factors towards technology use, and SRL strategies they adopt in learning. A qualitative description methodology using thematic analysis was used to identify key themes from the interview data. Results: Medical students reported the use of four types of technologies for learning: video resources (supporting rehearsal, elaboration and planning), review resources (supporting rehearsal, effort control, and self-assessment), management tools (supporting organization, elaboration, goal-setting, and time management), and social media (supporting help-seeking and effort regulation). Three key determinants of students’ self-initiated technology use were identified, which were: perceived usefulness, subjective norms, and educational compatibility. Conclusions: By probing medical students’ self-initiated technology use, SRL strategies, and determinants of technology use, this study suggested that in self-directed learning environment, medical students used a variety of third-party resources to facilitate learning and develop necessary learning strategies. This study also provided important implications for medical educators and instructional designers to better support students’ effective use of technologies for learning.

scholarly journals 1201 Performance Evaluation Of A Novel Contactless Breathing Monitor And Machine Learning Algorithm For Sleep Stage Classification In A Healthy Population

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A459-A459
Author(s):  
T Lauteslager ◽  
S Kampakis ◽  
A J Williams ◽  
M Maslik ◽  
F Siddiqui
Keyword(s):  
Machine Learning ◽  
Home Environment ◽  
Sleep Stage ◽  
Machine Learning Algorithms ◽  
Sleep Stages ◽  
Obstructive Sleep ◽  
Longitudinal Data Collection ◽  
Sleep Assessment ◽  
Stage Classification ◽  
Sleep Stage Classification

Abstract Introduction Although polysomnography (PSG) remains the gold standard for sleep assessment in a lab setting, non-EEG signals such as respiration and motion are directly affected by sleep stages and can be used for sleep stage prediction. Importantly, these signals can be obtained in a low-cost and unobtrusive manner, allowing for large scale and longitudinal data collection in a home environment. The Circadia C100 System (FDA 510(k) clearance expected Q1 2020) is a novel ‘nearable’ device that uses radar for contactless monitoring of respiration and motion. The current study aims to validate the performance of the associated sleep analysis algorithm. Methods A total of 41 nights of sleep data were recorded from 33 healthy participants using the device, alongside PSG. Data were recorded both in a sleep lab and home environment. PSG data were scored by RPSGT-certified technicians. Respiration and movement features were extracted, and machine learning algorithms were developed to perform sleep stage classification and predict sleep metrics. Algorithms were trained and validated on PSG data using cross-validation. Results An epoch-by-epoch true positive rate of 56.2%, 79.4%, 55.5% and 72.6% was found for ‘Wake’, ‘REM’, ‘Light’ and ‘Deep’ respectively. No statistical differences in performance were found between home-recorded and lab-recorded contactless data. Mean absolute error of total sleep time (TST), wake after sleep onset (WASO), and sleep efficiency (SE) was 13.2 minutes, 11.3 minutes and 3%, respectively. The contactless monitor was found to outperform both medical grade and clinical grade actigraphy based devices: The Philips Actiwatch Spectrum Plus and the Fitbit Alta HR. Conclusion Current results are encouraging and suggest that the contactless monitor could be used for long-term sleep assessment and continuous evaluation of sleep therapy outcomes. Further clinical validation work is ongoing in subjects diagnosed with sleep disorders such as obstructive sleep apnea. Support -

Cluster headache shows no association with rapid eye movement sleep

Cephalalgia ◽  
2012 ◽  
Vol 32 (4) ◽  
pp. 289-296 ◽  
Author(s):  
Sebastian Zaremba ◽  
Dagny Holle ◽  
Thomas E Wessendorf ◽  
Hans C Diener ◽  
Zaza Katsarava ◽  
...  
Keyword(s):  
Cluster Headache ◽  
Eye Movement ◽  
Rem Sleep ◽  
Sleep Stage ◽  
Sleep Time ◽  
Brain Regions ◽  
Sleep Stages ◽  
Rapid Eye Movement ◽  
Sleep State ◽  
Wake Time

Background: The connection of cluster headache (CH) attacks with rapid eye movement (REM) sleep has been suggested by various studies, while other authors challenge this assumption. We performed serial polysomnography to determine the association of nocturnal CH attacks and sleep. Methods: Five patients diagnosed with CH (two with the episodic and three with the chronic subtype) were included and studied over four consecutive nights to evaluate connections between attacks onset and sleep stage. Results: Twenty typical CH attacks were reported. Thirteen of these attacks arose from sleep. Seven attacks were reported after waking in the morning or shortly before going to sleep. The beginnings of sleep-related attacks were distributed arbitrarily between different non-REM sleep stages. No association of CH attacks with REM or sleep disordered breathing was observed. Increased heart rate temporally associated with transition from one sleep state to another was observed before patients awoke with headache. Total sleep time, total wake time, arousal index and distribution of non-REM sleep stages were different between chronic and episodic CH. Conclusion: CH attacks are not associated with REM sleep. Brain regions involved in sleep stage transition might be involved in pathophysiology of CH. Differences in sleep characteristics between subgroups might indicate adaptation processes or underlying pathophysiology.

scholarly journals Characterization of Mobile Work Zone Safety in Missouri

2020 ◽  
Vol 14 (1) ◽  
pp. 67-77
Author(s):  
Carlos Sun ◽  
Huang Feng ◽  
Yaw Adu-Gyamfi
Keyword(s):  
Time Of Day ◽  
Work Zone ◽  
Third Party ◽  
Contributory Factor ◽  
Speed Limit ◽  
Contributing Factors ◽  
Lane Changing ◽  
Mobile Work ◽  
Work Zone Safety ◽  
Areas Of Interest

Work zones often deviate from normal conditions in terms of geometrics (e.g. lane closure, narrow lanes), striping/markings, signs, and traffic. A Mobile Work Zone (MWZ) is a special category of a work zone where the location of the work zone keeps changing, often rapidly. Despite MWZ safety being of great interest to transportation agencies, they have not studied it formally. This paper presents an examination of MWZs and collisions involving Truck-Mounted Attenuators (TMAs). This examination utilized data fusion of three major databases from Missouri: crash reports, department of transportation claim reports, and MWZ schedules. The fused dataset involved 139 crashes from 2012-2017. The areas of interest included initial impact location, contributing factors, third-party versus employee fault, vehicle type, work zone activity, seasonality, speed limit, time of day, collision lane, and work train configuration. The majority of the crashes were the fault of third parties (>80%) and distraction/inattentiveness was the largest contributory factor (66%). Public outreach and education should emphasize on the difficulty in providing early warnings of MWZs. There is a significant percentage of crashes involving lane changing (39.2%) and even collision of the middle TMA truck (21.8%). Thus, it is important for the public to understand that an entire work train is an integral unit. Higher speed limit dominated MWZ crashes (>75%), even though they only represented 3.6% of the MWZs scheduled. The results of this study on MWZs provide some foundation for other researchers to pursue statistical modeling, assuming that a larger database of MWZ crashes could be developed.

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