scholarly journals An Automatic Estimation of the Rest-Interval for MotionWatch8© Using Uniaxial Movement and Lux Data

2020 ◽  
Author(s):  
Daniel Backhouse ◽  
Ryan Stanley Falck ◽  
Teresa Liu-Ambrose
Keyword(s):  
Older Adults ◽  
Sleep Duration ◽  
Light Exposure ◽  
Objective Measure ◽  
Self Report ◽  
Time Interval ◽  
Poor Sleep ◽  
Rest Interval ◽  
Scoring Method ◽  
Field Methods

Abstract Poor sleep is linked with chronic conditions common in older adults, including diabetes, heart disease, and dementia. Valid and reliable field methods to objectively measure sleep are thus greatly needed to examine how poor sleep impacts older adults. Wrist-worn actigraphy (WWA) is a common objective measure of sleep that uses motion and illuminance data to estimate sleep. The rest-interval marks the time interval between when an individual attempts to sleep and the time they get out of bed to start their day. Traditionally, the rest-interval is scored manually by trained technicians, however algorithms currently exist which automatically score WWA data, saving time and providing consistency from user-to-user. However, these algorithms ignore illuminance data and only considered motion in their estimation of the rest-interval. This study therefore examines a novel algorithm that uses illuminance data to supplement the approximation of the rest-interval from motion data. We examined a total of 1086 days of data of 129 participants who wore the MotionWatch8© WWA for ≥14 nights of observation. Resultant sleep measures from three different parameter settings were compared to sleep measures derived following a standard scoring protocol and self-report times. The algorithm showed the strongest correlation to the standard protocol (r= 0.92 for sleep duration). There were no significant differences in sleep duration, sleep efficiency and fragmentation index estimates compared to the standard scoring protocol. These results suggest that an automated rest-interval scoring method using both light exposure and acceleration data provides comparable accuracy to the standard scoring method.

scholarly journals An automatic estimation of the rest-interval for MotionWatch8© using uniaxial movement and lux data

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Daniel Backhouse ◽  
Ryan Stanley Falck ◽  
Teresa Liu-Ambrose
Keyword(s):  
Older Adults ◽  
Sleep Duration ◽  
Light Exposure ◽  
Objective Measure ◽  
Self Report ◽  
Time Interval ◽  
Poor Sleep ◽  
Rest Interval ◽  
Scoring Method ◽  
Field Methods

Abstract Background Poor sleep is linked with chronic conditions common in older adults, including diabetes, heart disease, and dementia. Valid and reliable field methods to objectively measure sleep are thus greatly needed to examine how poor sleep impacts older adults. Wrist-worn actigraphy (WWA) is a common objective measure of sleep that uses motion and illuminance data to estimate sleep. The rest-interval marks the time interval between when an individual attempts to sleep and the time they get out of bed to start their day. Traditionally, the rest-interval is scored manually by trained technicians, however algorithms currently exist which automatically score WWA data, saving time and providing consistency from user-to-user. However, these algorithms ignore illuminance data and only considered motion in their estimation of the rest-interval. This study therefore examines a novel algorithm that uses illuminance data to supplement the approximation of the rest-interval from motion data. Methods We examined a total of 1086 days of data of 129 participants who wore the MotionWatch8© WWA for ≥14 nights of observation. Resultant sleep measures from three different parameter settings were compared to sleep measures derived following a standard scoring protocol and self-report times. Results The algorithm showed the strongest correlation to the standard protocol (r = 0.92 for sleep duration). There were no significant differences in sleep duration, sleep efficiency and fragmentation index estimates compared to the standard scoring protocol. Conclusion These results suggest that an automated rest-interval scoring method using both light exposure and acceleration data provides comparable accuracy to the standard scoring method.

scholarly journals An Automatic Estimation of the Rest-Interval for MotionWatch8© Using Uniaxial Movement and Lux Data

2020 ◽  
Author(s):  
Daniel Backhouse ◽  
Ryan Stanley Falck ◽  
Teresa Liu-Ambrose
Keyword(s):  
Older Adults ◽  
Sleep Duration ◽  
Light Exposure ◽  
Objective Measure ◽  
Self Report ◽  
Time Interval ◽  
Poor Sleep ◽  
Rest Interval ◽  
Scoring Method ◽  
Field Methods

Abstract Background: Poor sleep is linked with chronic conditions common in older adults, including diabetes, heart disease, and dementia. Valid and reliable field methods to objectively measure sleep are thus greatly needed to examine how poor sleep impacts older adults. Wrist-worn actigraphy (WWA) is a common objective measure of sleep that uses motion and illuminance data to estimate sleep. The rest-interval marks the time interval between when an individual attempts to sleep and the time they get out of bed to start their day. Traditionally, the rest-interval is scored manually by trained technicians, however algorithms currently exist which automatically score WWA data, saving time and providing consistency from user-to-user. However, these algorithms ignore illuminance data and only considered motion in their estimation of the rest-interval. This study therefore examines a novel algorithm that uses illuminance data to supplement the approximation of the rest-interval from motion data. Methods: We examined a total of 1086 days of data of 129 participants who wore the MotionWatch8© WWA for ≥14 nights of observation. Resultant sleep measures from three different parameter settings were compared to sleep measures derived following a standard scoring protocol and self-report times. Results: The algorithm showed the strongest correlation to the standard protocol (r= 0.92 for sleep duration). There were no significant differences in sleep duration, sleep efficiency and fragmentation index estimates compared to the standard scoring protocol. Conclusion: These results suggest that an automated rest-interval scoring method using both light exposure and acceleration data provides comparable accuracy to the standard scoring method.

scholarly journals Refining sleep measurement using the Motionwatch8©: How many days of monitoring do we need to get reliable estimates of sleep quality for older adults with Mild Cognitive Impairment?

2020 ◽  
Author(s):  
Ryan S. Falck ◽  
Cindy K. Barha ◽  
Patrick C.Y. Chan ◽  
Teresa Liu-Ambrose
Keyword(s):  
Older Adults ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Sleep Duration ◽  
Older Adult ◽  
Cognitive Assessment ◽  
Cognitive Status ◽  
Field Methods ◽  
Sleep Measurement ◽  
Reliability Coefficients

Abstract Background Mild cognitive impairment (MCI) is a transition stage between healthy cognition and dementia, and is linked to poorer sleep. Objective, reliable, and low-burden field methods to measure older adult sleep are also currently needed. The MotionWatch8© (MW8) wrist-worn actigraph provides estimates of sleep with 14 days of observation; however, there may be underlying differences in the reliability of sleep estimates based on MCI status. We therefore investigated the number of MW8 monitoring days required to estimate sleep in older adults with MCI and without. Methods Older adults (55+ years; N=151) wore the MW8 for ≥14 days. The Montreal Cognitive Assessment was used to categorize participants with probable MCI (scores of <26/30) and participants without MCI (≥26/30). We calculated intra-class reliability coefficients for 1-, 7-, and 14-days of wear-time, and performed Spearman-Brown predictions to determine the number of monitoring days needed for an ICC=0.80. Results Older adults with MCI were older ( p <0.01), more likely to be male ( p =0.03), and had shorter sleep duration ( p <0.01). Spearman-Brown analyses indicated that the number of monitoring days needed for an ICC=0.80 in older adults with probable MCI was 7 days for sleep duration, 4 days for fragmentation, and 4 days for efficiency; adults without MCI required 4 days for duration, 6 days for fragmentation, and 3 days for efficiency. Conclusions Our results indicate that while the reliability of MW8 estimates of sleep differs based on cognitive status, 7 days of MW8 monitoring provides reliable estimates of sleep for adults with MCI and those without.

scholarly journals 0135 Self-Reported Sleep and Gut Microbiome Composition and Diversity: Associations in Well-Functioning Older Adults

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A53-A53
Author(s):  
C Holingue ◽  
N T Mueller ◽  
T Tanaka ◽  
M K Differding ◽  
C W Chia ◽  
...  
Keyword(s):  
Older Adults ◽  
Sleep Duration ◽  
Relative Abundance ◽  
Gut Microbiome ◽  
Rating Scale ◽  
Self Report ◽  
Microbiome Composition ◽  
Microbiome Diversity ◽  
Falling Asleep ◽  
Insomnia Symptoms

Abstract Introduction The gut microbiome is believed to play an important role in health and disease, yet little is known about the link between sleep and the gut microbiome in humans. We investigated the association of self-reported sleep with gut microbiome composition and diversity in a cohort of well-functioning older adults. Methods We studied 791 participants (mean age = 71.5±12.0 years, 55% women) in the Baltimore Longitudinal Study of Aging with self-report sleep measures and whole-genome DNA sequencing of stool samples. Predictors (modeled as continuous variables) included insomnia symptoms from the Women’s Health Initiative Insomnia Rating Scale (WHIIRS), sleep duration (&lt;5, 5–6, 6–7, &gt;7 hours), and frequency of excessive daytime sleepiness (EDS). We tested their association with gut microbiome diversity (Shannon index) and relative abundance of individual taxa using Kendall Tau Correlation. Next, we assessed whether these sleep variables were associated with overall microbiome structure (Bray-Curtis), adjusting for age, sex, race, education, BMI, depressive symptoms, and number of comorbidities. Results Sleep duration was associated with overall microbiome composition (p&lt;0.01), with longer sleep duration associated with lower biodiversity of microbes in the gut (p&lt;0.05). In phylum-level analyses, higher WHIIRS total (i.e., more severe insomnia) was associated with lower relative abundance of Actinobacteria, while more frequent EDS was associated with lower relative abundance of Fusobacteria. More frequent trouble falling asleep, staying asleep, early waking, poorer sleep quality and higher WHIIRS total were associated with lower abundance of Synergistetes (all p&lt;0.05). Conclusion In well-functioning older adults, self-reported sleep duration, symptoms of insomnia, and EDS were associated with microbiome diversity and composition. The phylum Synergistetes, which has been associated with protective humoral immune response in prior literature, may be an important correlate of insomnia symptoms in older adults. Future investigations are needed to examine the gut microbiome as a driver or mediator of sleep-health associations. Support This study was supported in part by National Institute on Aging (NIA) grant R01AG050507, the NIA Intramural Research Program (IRP), and Research and Development Contract HHSN-260-2004-00012C.

Visual attention and self-regulation of driving among older adults

2008 ◽  
Vol 20 (1) ◽  
pp. 162-173 ◽  
Author(s):  
Ozioma C. Okonkwo ◽  
Michael Crowe ◽  
Virginia G. Wadley ◽  
Karlene Ball
Keyword(s):  
Older Adults ◽  
Visual Attention ◽  
Social Engagement ◽  
Public Safety ◽  
Self Regulation ◽  
Significant Proportion ◽  
Objective Measure ◽  
Older Drivers ◽  
Self Report ◽  
Crash Risk

ABSTRACTBackground: With the number of older drivers increasing, self-regulation of driving has been proposed as a viable means of balancing the autonomy of older adults against the sometimes competing demand of public safety. In this study, we investigate self-regulation of driving among a group of older adults with varying functional abilities.Method: Participants in the study comprised 1,543 drivers aged 75 years or older. They completed an objective measure of visual attention from which crash risk was estimated, and self-report measures of driving avoidance, driving exposure, physical functioning, general health status, and vision. Crash records were obtained from the State Department of Public Safety.Results: Overall, participants were most likely to avoid driving in bad weather followed by driving at night, driving on high traffic roads, driving in unfamiliar areas, and making left-hand turns across oncoming traffic. With the exception of driving at night, drivers at higher risk of crashes generally reported greater avoidance of these driving situations than lower risk drivers. However, across all driving situations a significant proportion of higher risk drivers did not restrict their driving. In general, self-regulation of driving did not result in reduced social engagement.Conclusion: Some older drivers with visual attention impairments do not restrict their driving in difficult situations. There is a need for physicians and family members to discuss driving behaviors with older adults routinely to ensure their safety. The association between visual attention and driving restriction also has implications for interventions aimed at preserving mobility in the elderly.

scholarly journals Sleep and Olfaction among Older Adults

2017 ◽  
Vol 48 (3-4) ◽  
pp. 147-154 ◽  
Author(s):  
V. Eloesa McSorley ◽  
Jayant Pinto ◽  
L. Philip Schumm ◽  
Kristen Wroblewski ◽  
David Kern ◽  
...  
Keyword(s):  
Older Adults ◽  
Sleep Quality ◽  
Structural Equation Models ◽  
Sleep Problems ◽  
Community Dwelling ◽  
Odor Identification ◽  
Self Report ◽  
Poor Sleep ◽  
Wrist Actigraphy ◽  
Odor Sensitivity

Background: Sleep and olfaction are both critical physiological processes that tend to worsen with age. Decline in olfaction can be an early indicator of neurodegenerative diseases, whereas poor sleep quality is associated with reduced physical and mental health. Given associations with aging-related health declines, we explored whether variations in sleep were associated with olfactory function among older adults. Methods: We assessed the relationship between sleep characteristics and olfaction among 354 community-dwelling older adults. Olfaction was measured using a validated field and survey research tool. Sleep characteristics were measured using wrist actigraphy and with self-report of sleep problems. We fit structural equation models of latent constructs of olfaction based on olfactory task items and let this be a function of each sleep characteristic. Results: Actigraph sleep quality measures were associated with odor identification, but not with odor sensitivity. Longer duration sleepers had worse odor sensitivity compared to medium (58 h) sleepers, but sleep duration was not associated with odor identification. Reported sleep problems and reported usual duration were not associated with olfaction. Conclusions: Diminished sleep quality was associated with reduced capacity to identify odors. Determining whether this is a causal association will require further study and longitudinal data.

scholarly journals 0866 A Comparison Of Resting Cerebral Blood Flow And Sleep Quality In Older Adults

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A330-A330
Author(s):  
C C Hays ◽  
E A Almklov ◽  
H J Orff ◽  
C E Wierenga
Keyword(s):  
Older Adults ◽  
Blood Flow ◽  
Cerebral Blood Flow ◽  
Sleep Quality ◽  
Sleep Disturbances ◽  
Future Research ◽  
Aging Brain ◽  
Time Interval ◽  
Poor Sleep ◽  
Increased Risk

Abstract Introduction Sleep disturbances have been linked to a variety of health-related consequences, including clinically significant cognitive alterations. Older adults represent a particularly vulnerable population given that advanced age is associated with an increased risk for both sleep disorders, such as insomnia, and cognitive decline. Examining the relationship between resting cerebral blood flow (rCBF) and sleep quality in older adults will better our understanding of the neurophysiologic implications of poor sleep in aging adults. Methods Thirty-three cognitively normal older adults (15 males) between the ages of 65-85 (mean age=73) were administered the Pittsburg Sleep Quality Index (PSQI) and underwent assessment of rCBF using arterial spin labeling (ASL). Those who scored above 5 on the PSQI were defined as poor sleepers (n=17) and those who scored 5 or below were defined as good sleepers (n=16). Groups were then compared on voxel-wise whole-brain rCBF using independent samples t-tests statistically adjusting for age, sex, and the time interval between neuroimaging and sleep assessment. Results Compared to good sleepers, poor sleepers exhibited higher rCBF within bilateral thalamus and the left precuneus and lower rCBF within the left putamen (all ps&lt;.01, uncorrected). Conclusion In this preliminary investigation, poor sleepers exhibited a differential pattern of rCBF in several brain regions, including those involved in consciousness and other important cognitive abilities such as attention. Future research is needed to determine the short- and long-term implications of poor sleep on the aging brain. Support U.S. Department of Veterans Affairs Clinical Sciences Research and Development Service Merit Award 5I01CX000565 (CEW) & VA Rehabilitation Research & Development - Career Development Award - RX001512-01A2 (HJO)

scholarly journals Shining the Light on the MotionWatch8 Light Sensor for Sleep and Aging Research: What Can We Measure and What Are We Missing?

2021 ◽  
Vol 5 (1) ◽  
pp. 55-63
Author(s):  
Ryan S. Falck ◽  
Rachel A. Crockett ◽  
Jennifer C. Davis ◽  
Karim M. Khan ◽  
Teresa Liu-Ambrose
Keyword(s):  
Light Exposure ◽  
Bright Light ◽  
Light Therapy ◽  
Poor Sleep ◽  
Bright Light Therapy ◽  
Field Methods ◽  
Aging Research ◽  
Cut Points ◽  
Light Sensor ◽  
Receiver Operator Characteristics

Background: Poor sleep is common among older adults at risk for dementia and may be due to circadian dysregulation. Light is the most important external stimulus to the circadian clock and bright light therapy (BLT) has been used for >20 years to help realign circadian rhythms. However, the ability of field methods (e.g., actigraphy) to accurately determine the type and intensity of light is unknown. Objective: We examined the ability of the MotionWatch8 (MW8) light sensor to determine: 1) light versus dark, 2) electrical light versus daylight, and 3) device-based BLT versus light which was not BLT. Methods: We tested the MW8 under 17 daily light scenarios. Light exposure data was collected for 5 minutes during each scenario. Concurrently, we measured light exposure using the LT40 Light Meter, a sensitive measure of light intensity. We then developed individual cut-points using receiver operator characteristics analyses to determine optimal MW8 cut-points for 1) light versus dark; 2) electrical light versus daylight; and 3) light from a BLT box versus light which was not BLT. Bland-Altman plots tested the precision of the MW8 compared to the LT40. Results: The MW8 accurately discriminated light versus dark (>32 lux), and electrical light versus daylight (<323 lux). However, the MW8 had poor accuracy for 1) discriminating BLT from light which was not BLT; and 2) low precision compared to the LT40. Conclusion: The MW8 appears to be able to discern light versus dark and electrical light versus daylight; however, there remains a need for accurate field methods capable of measuring light exposure.

scholarly journals Night-to-Night Associations Between Light Exposure and Sleep Health

2021 ◽  
Author(s):  
Michael Mead ◽  
Kathryn Reid ◽  
Kristen Knutson
Keyword(s):  
Sleep Duration ◽  
Light Exposure ◽  
Poor Sleep ◽  
Sleep Health ◽  
Cross Sectional ◽  
Wake Time ◽  
Light Levels ◽  
Fragmentation Index ◽  
Multi Level ◽  
Offset Time

Previous research has demonstrated that exposure to light preceding and during sleep is associated with poor sleep, but most research to date has utilized either experimental or cross-sectional designs. The current study expands upon prior studies by using a microlongitudinal design that examines the night-to-night associations between light and sleep health in a diverse sample of adults (pre-registered at osf.io/k5zgv). U.S. adults aged 18 to 87 from two parent studies (N= 124) wore an actiwatch for up to 10 nights. Light variables estimated from actigraphy include both average exposure and time above light threshold of 10 (TALT10) and 40 (TALT40) lux both during sleep and for the 1-hour preceding sleep. Actigraphy-based sleep variables included sleep offset, duration, percentage, and fragmentation index. Higher average light exposure during sleep was associated with a later sleep offset time, lower sleep percentage, and higher fragmentation index (all p &lt;.01). More minutes of TALT10 during sleep was associated with later sleep timing, lower sleep percentage, and higher fragmentation index (all p &lt; .01) and greater TALT40 during sleep was associated with lower sleep percentage. Light exposure was not related to sleep duration. In summary, greater light exposure during sleep was related to poorer sleep continuity and later wake time. The lack of association between light and sleep duration may be the result of compensating for sleep disruption by delaying wake time. Multi-level interventions to consistently reduce light levels during sleep should be considered.

An Optimal Self-Report Physical Activity Measure for Older Adults: Does Physical Function Matter?

2020 ◽  
pp. 1-7
Author(s):  
Nancy W. Glynn ◽  
Alexa J. Meinhardt ◽  
Kelsea R. LaSorda ◽  
Jessica L. Graves ◽  
Theresa Gmelin ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Physical Function ◽  
Objective Measure ◽  
The Elderly ◽  
Community Dwelling ◽  
Self Report ◽  
Sensewear Armband ◽  
Physical Activity Measure ◽  
Community Dwelling Older Adults

The authors compared two self-report measures of physical activity, the Physical Activity Scale for the Elderly (PASE) and the Community Healthy Activities Model Program for Seniors (CHAMPS), against the device-derived SenseWear Armband (SWA), to identify a recommended self-report tool to measure physical activity in older adults across physical function levels. A total of 65 community-dwelling older adults completed the PASE, CHAMPS, and seven full days of SWA wear. The authors measured physical function using the modified short physical performance battery (SPPB) and a usual-paced 6-m walk. Age- and sex-adjusted Spearman correlations showed that CHAMPS and SWA were correlated in higher functioning participants (SPPB: ρ = .33, p = .03; gait speed: ρ = .40, p = .006) and also correlated in lower functioning participants for SPPB (ρ = .70, p = .003) only. PASE and SWA were not significantly correlated across physical function. When an objective measure of physical activity is not practical, the CHAMPS questionnaire appears to capture physical activity for older adults across physical function levels.

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