Sleep estimation from wrist activity in patients with major depression

The actigraphic evaluation of daytime sleep in central disorders of hypersomnolence: comparison with polysomnography

STUDY OBJECTIVES

The role of actigraphy in central disorders of hypersomnolence (CDH) is expanding but evidence of reliability with polysomnography (PSG) is scarce and provided only during nighttime. We explored the agreement between actigraphy and continuous 24-hour PSG at CDH diagnosis.

METHODS

Forty-four consecutive drug-naïve patients (28 narcolepsy, 16 idiopathic hypersomnia) underwent actigraphy during 24 hours of free-running PSG, during multiple sleep latency test (MSLT) and 13 of them also during maintenance of wakefulness test (MWT). Daytime and nighttime sleep features and MSLT and MWT mean sleep latencies (mSL) were estimated with the actigraphic algorithms by Cole-Kripke (CK) Sadeh, and University of California San Diego (UCSD). Agreement to corresponding PSG measures was assessed with Bland Altman plots.

RESULTS

Nighttime-total sleep time (TST) in narcolepsy was significantly underestimated with CK (bias 27.8 min, 95%CI 13.7-41.9) and Sadeh (bias 56.7 min, 95%CI 38.8/74.5). Daytime-TST was overestimated in IH and narcolepsy with all algorithms (CK: bias -42.2, 95%CI -67/-17.4; Sadeh: bias -30.2 min, 95%CI -52.7/-7.7; UCSD bias -86.9 min, 95%CI -118.2/-55.6). 24-hour-TST was overestimated by CK and UCSD in IH (CK: bias -58.5 min, 95%CI -105.5/-11.5; UCSD: bias -118.8 min, 95% CI -172.5/-65), and by UCSD in narcolepsy (bias -68.8 min, 95%CI -109.3/-38.2). In the entire cohort, actigraphy overestimated MSLT mSL but not MWT mSL.

CONCLUSIONS

Conventional actigraphic algorithms overestimate 24-hour TST in IH and underestimate nighttime TST in narcolepsy. These discrepancies call for cautious application of actigraphy in the diagnostic process of CDH and the development of new quantitative signal analysis approaches.

A novel method to increase specificity of sleep-wake classifiers based on wrist-worn actigraphy

The knowledge of the distribution of sleep and wake over a 24-h day is essential for a comprehensive image of sleep-wake rhythms. Current sleep-wake scoring algorithms for wrist-worn actigraphy suffer from low specificities, which leads to an underestimation of the time staying awake. The goal of this study (ClinicalTrials.gov Identifier: NCT03356938) was to develop a sleep-wake classifier with increased specificity. By artificially balancing the training dataset to contain as much wake as sleep epochs from day- and nighttime measurements from 12 subjects, we optimized the classification parameters to an optimal trade-off between sensitivity and specificity. The resulting sleep-wake classifier achieved high specificity of 80.4% and sensitivity of 88.6% on the balanced dataset containing 3079.9 h of actimeter data. In the validation on night sleep of separate adaptation recordings from 19 healthy subjects, the sleep-wake classifier achieved 89.4% sensitivity and 64.6% specificity and estimated accurately total sleep time and sleep efficiency with a mean difference of 12.16 min and 2.83%, respectively. This new, device-independent method allows to rid sleep-wake classifiers from their bias towards sleep detection and lay a foundation for more accurate assessments in everyday life, which could be applied to monitor patients with fragmented sleep-wake rhythms.

A comparison of agreement between actigraphy and polysomnography for assessing sleep during posttraumatic amnesia

STUDY OBJECTIVES

Sleep disturbance often emerges in the early recovery phase following a moderate to severe traumatic brain injury, known as posttraumatic amnesia. Actigraphy is commonly employed to assess sleep, as it is assumed that patients in posttraumatic amnesia (who display confusion, restlessness, and agitation) would better tolerate this measure over gold-standard polysomnography (PSG). This study evaluated the agreement between PSG and actigraphy for determining (sleep/wake time, sleep efficiency, sleep latency, and awakenings) in patients experiencing posttraumatic amnesia. It also compared the epoch-by-epoch sensitivity, specificity, and accuracy between the Actigraph device's 4 wake threshold settings (low, medium, high, and automatic) to PSG.

METHODS

The sample consisted of 24 inpatients recruited from a traumatic brain injury inpatient rehabilitation unit. Ambulatory PSG was recorded overnight at bedside and a Philips Actiwatch was secured to each patient's wrist for the same period.

RESULTS

There were poor correlations between PSG and actigraphy for all parameters (Lin's concordance correlation coefficient = < 0.80). The low threshold displayed the highest correlation with PSG for wake and sleep time, albeit still low. Actigraphy displayed low specificity (ranging from 17.1% to 36.6%). There appears to be a greater disparity between actigraphy and PSG for patients with increased wake time.

CONCLUSIONS

Actigraphy, while convenient, demonstrated poorer performance in determining sleep-wake parameters in patients with significantly disturbed sleep. Ambulatory PSG can provide a clearer understanding of the extent of sleep disturbances in these patients with reduced mobility during early rehabilitation. Study findings can help design future protocols of sleep assessment during posttraumatic amnesia and optimize treatment.

CITATION

Fedele B, McKenzie D, Williams G, Giles R, Olver J. A comparison of agreement between actigraphy and polysomnography for assessing sleep during posttraumatic amnesia. J Clin Sleep Med. 2022;18(11):2605-2616.

The Effect of Bright Light Therapy on Sleep and Quality of Life in Patients With Poststroke Insomnia

OBJECTIVE

Poststroke insomnia is common and negatively affects stroke recovery. The objective of this study was to determine the effectiveness of bright light therapy for mild-to-moderate stroke patients with insomnia.

METHODS

This study was randomized, double blind, and placebo controlled. A 2-week trial was conducted on patients with mild-to-moderate stroke who had poststroke insomnia. Only patients who had experienced a first episode of stroke were enrolled in this study. Sleep parameters were measured using the Actiwatch Spectrum Pro for 7 days before and after light therapy. The instrument specifically collected data concerning sleep, mood state, fatigue, and subjective quality of life. Participants with poststroke insomnia received bright light therapy (10,000 lux) or placebo therapy for 30 minutes in the early morning. A total of 112 eligible participants entered the study, but only 56 patients were randomized to treatment (27 to bright light therapy and 29 to placebo therapy).

RESULTS

Results from analysis of variance showed that the mean change of sleep latency (F(1,55) =4.793, p = .033) and sleep efficiency (F(1,55) = 5.625, p = .022) were significantly superior in bright light therapy over placebo. Bright light therapy resulted in significant improvements in daytime sleepiness, fatigue, mood, and quality of life in study participants (p < .05).

CONCLUSIONS

Bright light therapy is a nonpharmacological treatment of early, poststroke insomnia in patients who had a mild to moderate stroke. In addition, bright light therapy is effective for the treatment of daytime sleepiness, fatigue, and depression and for improving quality of life in patients with poststroke insomnia.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT04721574.

Maternal Bonding Predicts Actigraphy-Measured Sleep Parameters in Depressed and Nondepressed Adults

Associations between subjective maternal bonding recalled from the first 16 years of life and current sleep indices were investigated in a clinical sample of 34 adults with major depressive disorder and 36 normal controls (n = 70) using the self-report parental bonding instrument and wrist actigraphy. Results of multiple linear regression analyses indicated that reports of maternal bonding indices were associated with several sleep indices in adulthood independent of depression status. Higher levels of maternal care were associated with greater time in bed and total sleep time. Higher levels of maternal overprotection were associated with fewer awakenings. Findings indicate that reported maternal bonding characteristics in childhood are related to objectively measured sleep characteristics in adulthood, independent of mood state.

Smartphone-Based Tracking of Sleep in Depression, Anxiety, and Psychotic Disorders

PURPOSE OF REVIEW

Sleep is an important feature in mental illness. Smartphones can be used to assess and monitor sleep, yet there is little prior application of this approach in depressive, anxiety, or psychotic disorders. We review uses of smartphones and wearable devices for sleep research in patients with these conditions.

RECENT FINDINGS

To date, most studies consist of pilot evaluations demonstrating feasibility and acceptability of monitoring sleep using smartphones and wearable devices among individuals with psychiatric disorders. Promising findings show early associations between behaviors and sleep parameters and agreement between clinic-based assessments, active smartphone data capture, and passively collected data. Few studies report improvement in sleep or mental health outcomes. Success of smartphone-based sleep assessments and interventions requires emphasis on promoting long-term adherence, exploring possibilities of adaptive and personalized systems to predict risk/relapse, and determining impact of sleep monitoring on improving patients' quality of life and clinically meaningful outcomes.

Agreement between actigraphic and polysomnographic measures of sleep in adults with and without chronic conditions: A systematic review and meta-analysis

Wrist actigraphy (ACT) may overestimate sleep and underestimate wake, and the agreement may be lower in people with chronic conditions who often have poor sleep and low activity levels. The purpose of this systematic review is to compare the agreement between ACT and polysomnographic (PSG) measures of sleep in adults without chronic conditions and sleep complaints (healthy) and with chronic conditions. We conducted a systematic review and meta-analysis using PRISMA guidelines. We searched PubMed, OVIDEMBASE, OVIDMEDLINE, OVIDPsycINFO, CENTRAL, CINAHL, ClinicalTrials.gov, International Clinical Trials Registry, and Open Grey. We included 96 studies with a total of 4134 participants, of whom 762 (18.4) were healthy adults and 724 (17.5%) were adults with chronic conditions. Among adults with chronic conditions, ACT overestimated TST, compared to PSG [M = 22.42 min (CI 95%: 11.92, 32.91 min)] and SE [M = 5.21% (CI 95%: 1.41%-9.00%)]. ACT underestimated SOL [M = -7.70 min (CI 95%: -15.22, -0.18 min)], and WASO [M = -10.90 min (CI 95%: -26.01, 4.22 min)]. These differences were consistently larger between ACT and PSG sleep measures compared to healthy adults. Research is needed to better understand factors that influence the agreement between ACT and PSG among people with chronic conditions.

Discrepancy between wrist-actigraph and polysomnographic measures of sleep in patients with stable heart failure and a novel approach to evaluating discrepancy

Wrist-actigraphy is often used to measure sleep characteristics in a variety of populations, but discrepancies between actigraphic and polysomnographic measures have been noted in populations experiencing poor sleep quality. The purpose of this study is to examine the discrepancy between these measures and risk factors for discrepancy in people with heart failure using a novel index. We used sleep measures simultaneously recorded by actigraphy and polysomnography, and clinical data from a cross-sectional study of 155 patients with heart failure (age = 60.5 [16.1] years; 65.2% male) recruited from evidence-based heart failure disease management programmes. The discrepancy and consistency between the two measures were evaluated using Bland-Altman plots, intra-class correlations and a newly developed index that represents activity counts in wake episodes. Overall, participants had short total sleep time (327.7 [95.9] min) and poor sleep efficiency (71.3 [16.0]%) on polysomnography. The discrepancies between sleep measures were small in patients less than 60 years old, and there was excellent consistency (intra-class correlation = 0.81) compared with older patients who had poorer consistency (intra-class correlation = 0.53) on total sleep time. Higher daytime motor activity, poor sleep quality and more severe insomnia were associated with smaller discrepancies in older, but not younger, patients, and associations were more sensitively detected by the new index. These findings suggest the importance of aging, disability and co-morbidity that may influence motor activity from which sleep estimates are scored with actigraphy. The new index may be useful in identifying factors associated with the correspondence between actigraphy and polysomnography.

Calibrating actigraphy to improve sleep efficiency estimates

Actigraphy (ACT) can enhance treatment for insomnia by providing objective estimates of sleep efficiency; however, only two studies have assessed the accuracy of actigraphy-based estimates of sleep efficiency (ACT-SE) in sleep-disordered samples studied at home. Both found poor correspondence with polysomnography-based estimates (PSG-SE). The current study tested that concordance in a third sample and piloted a method for improving ACT-SE. Participants in one of four diagnostic categories (panic disorder, post-traumatic stress disorder, comorbid post-traumatic stress and panic disorder and controls without sleep complaints) underwent in-home recording of sleep using concurrent ambulatory PSG and actigraphy. Precisely synchronized PSG and ACT recordings were obtained from 41 participants. Sleep efficiency was scored independently using conventional methods, and ACT-SE/PSG-SE concordance examined. Next, ACT data recorded initially at 0.5 Hz were resampled to 30-s epochs and rescaled on a per-participant basis to yield optimized concordance between PSG- and ACT-based sleep efficiency estimates. Using standard scoring of ACT, the correlation between ACT-SE and PSG-SE across participants was statistically significant (r = 0.35, P < 0.025), although ACT-SE failed to replicate a main effect of diagnosis. Individualized calibration of ACT against a night of PSG yielded a significantly higher correlation between ACT-SE and PSG-SE (r = 0.65, P < 0.001; z = 1.692, P = 0.0452, one-tailed) and a significant main effect of diagnosis that was highly correspondent with the effect on PSG-SE. ACT-based estimates of sleep efficiency in sleep-disordered patients tested at home can be improved significantly by calibration against a single night of concurrent PSG.

Reduced Tolerance to Night Shift in Chronic Shift Workers: Insight From Fractal Regulation

Study Objectives

Healthy physiology is characterized by fractal regulation (FR) that generates similar structures in the fluctuations of physiological outputs at different time scales. Perturbed FR is associated with aging and age-related pathological conditions. Shift work, involving repeated and chronic exposure to misaligned environmental and behavioral cycles, disrupts circadian coordination. We tested whether night shifts perturb FR in motor activity and whether night shifts affect FR in chronic shift workers and non-shift workers differently.

Methods

We studied 13 chronic shift workers and 14 non-shift workers as controls using both field and in-laboratory experiments. In the in-laboratory study, simulated night shifts were used to induce a misalignment between the endogenous circadian pacemaker and the sleep-wake cycles (ie, circadian misalignment) while environmental conditions and food intake were controlled.

Results

In the field study, we found that FR was robust in controls but broke down in shift workers during night shifts, leading to more random activity fluctuations as observed in patients with dementia. The night shift effect was present even 2 days after ending night shifts. The in-laboratory study confirmed that night shifts perturbed FR in chronic shift workers and showed that FR in controls was more resilience to the circadian misalignment. Moreover, FR during real and simulated night shifts was more perturbed in those who started shift work at older ages.

Conclusions

Chronic shift work causes night shift intolerance, which is probably linked to the degraded plasticity of the circadian control system.

What Engineering Technology Could Do for Quality of Life in Parkinson's Disease: A Review of Current Needs and Opportunities

Parkinson's disease (PD) involves well-known motor symptoms such as tremor, rigidity, bradykinesia, and altered gait, but there are also nonlocomotory motor symptoms (e.g., changes in handwriting and speech) and even nonmotor symptoms (e.g., disrupted sleep, depression) that can be measured, monitored, and possibly better managed through activity-based monitoring technologies. This will enhance quality of life (QoL) in PD through improved self-monitoring and also provide information that could be shared with a healthcare provider to help better manage treatment. Until recently, nonmotor symptoms ("soft signs") had been generally overlooked in clinical management, yet these are of primary importance to patients and their QoL. Day-to-day variability of the condition, the high variability in symptoms between patients, and the isolated snapshots of a patient in periodic clinic visits make better monitoring essential to the proper management of PD. Continuously monitored patterns of activity, social interactions, and daily activities could provide a rich source of information on status changes, guiding self-correction and clinical management. The same tools can be useful in earlier detection of PD and will improve clinical studies. Remote medical communications in the form of telemedicine, sophisticated tracking of medication use, and assistive technologies that directly compensate for disease-related challenges are examples of other near-term technology solutions to PD problems. Ultimately, a sensor technology is not good if it is not used. The Parkinson's community is a sophisticated early adopter of useful technologies and a group for which engineers can provide near-term gratifying benefits.

Short-term effects of electroconvulsive therapy on subjective and actigraphy-assessed sleep parameters in severely depressed inpatients

Background. Sleep disturbances are a key feature of major depression. Electroconvulsive treatment (ECT) may improve polysomnography-assessed sleep characteristics, but its short-term effects on actigraphy-assessed and subjective sleep characteristics are unknown. We therefore aimed to assess the effects of ECT on subjective and objective sleep parameters in a proof-of-principle study. Methods. We assessed subjective and objective sleep parameters in 12 severely depressed patients up to 5 consecutive days during their ECT course, corresponding to a total of 43 nights (including 19 ECT sessions). The 12 patients were 83% female and on average 62 (standard deviation (SD) 14) years old and had an average MADRS score of 40 at baseline (SD 21). Results. Subjective and objective sleep parameters were not directly affected by ECT. The subjective sleep efficiency parameter was similar on the day after ECT and other days. ECT did not affect the number of errors in the Sustained Attention to Response Task. Patients subjectively underestimated their total sleep time by 1.4 hours (P < 0.001) compared to actigraphy-assessed sleep duration. Conclusion. ECT did not affect subjective and actigraphy-assessed sleep in the short term. Depressed patients profoundly underestimated their sleep duration.

Quantitative evaluation of the use of actigraphy for neurological and psychiatric disorders

Quantitative and objective evaluation of disease severity and/or drug effect is necessary in clinical practice. Wearable accelerometers such as an actigraph enable long-term recording of a patient's movement during activities and they can be used for quantitative assessment of symptoms due to various diseases. We reviewed some applications of actigraphy with analytical methods that are sufficiently sensitive and reliable to determine the severity of diseases and disorders such as motor and nonmotor disorders like Parkinson's disease, sleep disorders, depression, behavioral and psychological symptoms of dementia (BPSD) for vascular dementia (VD), seasonal affective disorder (SAD), and stroke, as well as the effects of drugs used to treat them. We believe it is possible to develop analytical methods to assess more neurological or psychopathic disorders using actigraphy records.

Biological rhythms and mood disorders

Integration of several approaches concerning time and temporality can enhance the pathophysiological study of major mood disorders of unknown etiology. We propose that these conditions might be interpreted as disturbances of temporal profile of biological rhythms, as well as alterations of time-consciousness. Useful approaches to study time and temporality include philological suggestions, phenomenological and psychopathological conceptualizatíons, clinical descriptions, and research on circadian and ultradían rhythms, as well as nonlinear dynamics approaches to their analysis.

Sleep in America: role of racial/ethnic differences

Sleep duration in America has gradually declined over the last four decades and appears to have reached a plateau for the last six years, with recent studies reporting that the population's current average sleep duration is approximately 6 h. In this paper, we examine epidemiologic and community-based data on sleep complaints reported by American adults, specifically addressing the role of race/ethnicity in the subjective report of sleep problems. Subjective and objective findings indicate that black (throughout the text, we use the term black in lieu of African American for there are instances where we refer to individuals with self-ascribed race/ethnicity as black, African American, African, or Caribbean American; the term white is used to denote individuals of European descent). Americans have higher rates of long (≥9 h) and short (≤5 h) sleep than their white counterparts, and this may mediate a higher risk of cardiovascular disease, obesity and diabetes among blacks. In addition, studies show mixed results on sleep complaints among blacks compared to those among other ethnicities. This paper explores factors that may contribute to racial/ethnic differences in sleep including intra-ethnic variation, cultural biases, genetics and psychosocial factors.

Actigraphy monitoring of symptoms in patients with Parkinson's disease

Although the Unified Parkinson's Disease Rating Scale (UPDRS) is the "gold-standard" tool in assessing the severity of symptoms in patients with Parkinson's disease (PD), not all activity-related disease symptoms can be accurately captured by the well-established clinical rating scale. Using an alternative approach, this study examined the level of physical activity measured by actigraphy over time and whether change in physical activity was associated with disease severity assessed by UPDRS. We used a longitudinal design in which physical activity and disease severity were assessed repeatedly during a 4-month interval, over a 3-year observational period, in a sample of 61 patients with idiopathic PD and a control group of 32 neurologically intact individuals. Physical activity data during awake-time were analyzed using the power-law exponent (PLE) method. Correlational relationships between changes in maxima values of PLE and scores of total UPDRS, UPDRS-part II (Activities of Daily Living), and UPDRS-part III (Motor Examination) in patients with PD were examined. Results show an increase in maxima values of PLE and the UPDRS total score in PD patients and that there is a positive association between changes in maxima values and total UPDRS score (r=0.746, p=0.032), UPDRS-part II score (r=0.687, p=0.027), and UPDRS-part III score (r=0.893, p=0.018). There was no significant change in the level of physical activity over time for the controls. Findings from this study indicate that change in physical activity, as captured by actigraphy, is associated with increased severity in patients' clinical symptoms of PD over time. Thus, these data suggest that, when used in conjunction with the conventional UPDRS measure, an actigraphic measure of physical activity may provide clinicians an adjunct measurement approach to monitor patients' activity-based disease progression or responses to treatment in outpatient clinic settings.

Factors that may influence the classification of sleep-wake by wrist actigraphy: the MrOS Sleep Study

STUDY OBJECTIVES

Total sleep time (TST), sleep efficiency (SE), sleep latency (SOL) and wake after sleep onset (WASO) assessed by actigraphy gathered in 3 different modes were compared to polysomnography (PSG) measurements to determine which mode corresponded highest to PSG. Associations of measurement error for TST (PSG-actigraphy) with demographics, medical history, exam data, and sleep characteristics were examined.

METHODS

Participants underwent in-home 12-channel PSG. Actigraphy data were collected in 3 modes: proportional integration mode (PIM), time above threshold (TAT) and zero crossings mode (ZCM). The analysis cohort was a subgroup of 889 men (mean age 76.4 years) from the MrOS Sleep Study with concurrently measured PSG and actigraphy. Intraclass correlation coefficients (ICCs) were used to compare the association between PSG and actigraphy.

RESULTS

The PIM mode of actigraphy corresponded moderately to PSG for all measures (ICCs 0.32 to 0.57), TAT a little lower (ICCs 0.17 to 0.47), and ZCM lower still (ICCs 0.16 to 0.33). The PIM mode corresponded best to PSG (ICCs TST 0.57; SE 0.46; SOL 0.23; WASO 0.54), though the estimations from PSG and PIM mode differed significantly (p < 0.01). The PIM mode overestimated TST by 13.2 min on average, but underestimated TST for those in certain subgroups: those with excessive daytime sleepiness, less sleep fragmentation, or more sleep disordered breathing (p < 0.05).

CONCLUSIONS

Sleep parameters from the PIM and TAT modes of actigraphy corresponded reasonably well to PSG in this population, with the PIM mode correlating highest. Systematic measurement error was observed within subgroups with different sleep characteristics.

Actigraphic assessment of a polysomnographic-recorded nap: a validation study

This study aimed to determine if actigraphy could differentiate sleep and wake during a daytime nap and no-nap rest period. Fifty-seven subjects participated in the study; 30 subjects were in the nap group and the remaining 27 in the no-nap comparison group. All subjects wore actigraphs while simultaneously undergoing polysomnography (PSG). Three actigraphic sensitivity levels (high, medium, low) and two interval duration minimums (15 and 40 min) were used to score the nap and no-nap data. The variables examined included total sleep time (TST), sleep latency (SL), wake after sleep onset (WASO) and sleep efficiency (SE). The Bland-Altman technique was used to determine concordance. Epoch-by-epoch analysis examined actigraphic accuracy, sensitivity and specificity. For the naps, all actigraph settings except low-40 showed significant correlations with TST. The high and medium settings predicted SE significantly and the high settings predicted SL significantly. Bland-Altman analyses demonstrated high settings overestimated TST while high and medium settings overestimated SE. Overall, for the nap condition accuracy for the actigraph was 82-86%, sensitivity was 92-96% and specificity was 40-67%. In the no-nap condition, accuracy for the actigraph was 60-84%, sensitivity was 47-78% and specificity was 60-86%. Medium-40 and low-40 were the only settings that did not misidentify sleep in the no-nap condition. These results suggest that actigraphy can predict TST, SE and SL reliably, depending upon parameter settings, and actigraphy is a highly sensitive but not specific measure for daytime naps. Different actigraphy settings may be optimal depending upon the variables of interest. Discrimination of sleep and wake during periods of waking quiescence is not as robust as during periods of mainly daytime sleep.

Actigraphic assessment of daily sleep-activity pattern abnormalities reflects self-assessed depression and anxiety in outpatients with advanced non-small cell lung cancer

OBJECTIVES

We measured subjectively evaluated depression and anxiety, and objectively measured daily sleep-activity patterns in inpatients and outpatients with advanced non-small cell lung cancer (NSCLC) and determined whether cancer-associated depression and anxiety are accompanied by characteristic circadian rhythm abnormalities.

METHODS

Equal numbers of inpatients (n=42) and outpatients (n=42) with advanced NSCLC were studied. Baseline depression and anxiety, assessed by the Hospital Anxiety and Depression Scale (HADS), and actigraphy were recorded before chemotherapy initiation. The effects of the presence and severity of chronic obstructive pulmonary disease (COPD) on depression, anxiety, and actigraphy were assessed only among the 42 outpatients.

RESULTS

Anxiety occurred in 40% and depression in 25% of these lung cancer patients, equally among inpatients and outpatients. All patients suffer extremely disturbed daily sleep-activity cycles but each patient also maintains some degree of circadian organization. Outpatients maintain more robust daily activity patterns and longer, more consolidated nighttime sleep compared with inpatients. The more disrupted the daily sleep-activity rhythm, the worse the depression and/or anxiety scores for outpatients. These relationships are obscured among inpatients. COPD has no independent measurable effects on the daily organization of sleep-activity, depression, or anxiety.

CONCLUSIONS

Lung cancer patients whose diurnal activity is disturbed by prolonged and frequent sedentary episodes and whose sleep is disturbed by frequent and prolonged waking are most anxious and depressed. These findings and relationships are masked by hospitalization. Since diurnal exercise improves both sleep and mood, it is reasonable to test whether enhancing daytime activity and nighttime sleep can diminish cancer-associated depression.

Longitudinal changes of day-time and night-time gross motor activity in clinical responders and non-responders of major depression

Psychomotor retardation (PR) is among the most important features of depression. This study investigates the development of day- and night-time as well as intensity and quantity of circadian motor activity during a 4-week course of treatment among 27 patients with depression compared to 27 healthy controls. A diagnosis of major depression was made using SCID. Motor activity was continuously measured with an actigraph during the study and clinical course of depression with HAM-D-21. Motor activity was described as the quantity and intensity of movements during day- and night- time. Clinically improved patients had significantly intensified movements after 4 weeks, compared to subjects with <50% improvement on HAM-D. While the measures of day-time level of movements captured the clinical improvement of depression, clinical improvement was not reflected by the night-time measurements. This study demonstrates that the separated analysis of level and quantity of movements supports a better understanding of the nature of psychomotor retardation during depression. The subdivision in day- and night-time activity objectively measured with actigraphy captures distinct patterns of motor activity and represents prognostic factors in the treatment outcome of depression. The study also highlights the importance of studying the intensity of movements separately from the quantity of movements in relation to treatment outcome.

Autonomic activation during sleep in posttraumatic stress disorder and panic: a mattress actigraphic study

BACKGROUND

While it has been reported that persons with posttraumatic stress disorder (PTSD) manifest tonic autonomic activation, the literature contains numerous counterexamples. In revisiting the question, this study employed a novel method of mattress actigraphy to unobtrusively estimate heart rate and respiratory sinus arrhythmia over multiple nights of sleep in the home.

METHODS

Sleep cardiac autonomic status was estimated in four diagnostic groups, posttraumatic stress disorder, panic disorder, persons comorbid for both conditions, and control subjects. All 59 participants were community-residing nonveterans screened for sleep apnea and periodic leg movement disorder with polysomnography. Heart rate and respiratory sinus arrhythmia were calculated from the kinetocardiogram signal measured via accelerometers embedded in a mattress topper. Times in bed and asleep were also estimated. Per participant data were obtained from a median of 12 nights.

RESULTS

Both posttraumatic stress disorder and posttraumatic stress disorder/panic disorder comorbid groups exhibited significantly higher heart rates and lower respiratory sinus arrhythmia magnitudes than panic disorder participants and control subjects. Panic disorder participants were indistinguishable from control subjects. The PTSD-only group exhibited longer times in bed and longer times presumably asleep than the other three groups.

CONCLUSIONS

In this study, posttraumatic stress disorder, but not panic disorder, was associated with altered cardiac autonomic status during sleep. Among participants meeting criteria for PTSD alone, autonomic activation co-occurred with prolongation of actigraphic sleep.

Sleep patterns and psychological distress in women living in an inner city

Psychological distress, including symptoms of anxiety, depression, and psychological trauma, is common in women living in inner cities and can be associated with disturbed sleep. The purposes of the study of 115 women were to examine: (a) objective and subjective sleep patterns; (b) extent of psychological distress; and (c) the relationship between objective and subjective sleep patterns and psychological distress. Wrist actigraphs were worn. High levels of life stress, sleep pattern disturbance, and psychological distress were common. Self-reported sleep patterns, but not objective sleep pattern variables, explained 12.5% to 44% of the variance in psychological distress, suggesting the importance of screening for sleep and psychological distress. These findings suggest that interventions focusing on sleep or psychological distress may reduce symptoms.

Reduction of scale invariance of activity fluctuations with aging and Alzheimer's disease: Involvement of the circadian pacemaker

Human motor control systems orchestrate complex scale-invariant patterns of activity over a wide range of time scales (minutes to hours). The neural mechanisms underlying scale-invariance are unknown in humans. In rats, the master circadian pacemaker [suprachiasmatic nucleus (SCN)] is crucially involved in scale-invariant activity fluctuations over multiple time scales from minutes to 24 h. Aging and Alzheimer's disease (AD) are associated with progressive dysfunction of the SCN. Thus, if the SCN is responsible for the scale-invariant activity fluctuations in humans, we predict disturbances of scale-invariant activity fluctuations in elderly humans and even more pronounced disturbances in elderly humans with AD. To test these hypotheses, we studied spontaneous daytime activity patterns in 13 young adults (mean +/- SD: 25.5 +/- 6.1 y); 13 elderly people with early-stage AD (68.5 +/- 6.1 y) matched with 13 elderly controls (68.6 +/- 6.1 y); and 14 very old people with late-stage AD (83.9 +/- 6.7 y) matched with 12 very old controls (80.8 +/- 8.6 y). In young adults, activity exhibited robust scale-invariant correlations across all tested time scales (minutes to 8 h). The scale-invariant correlations at 1.5-8 h declined with age (P = 0.01) and were significantly reduced in the elderly (P = 0.04) and very old controls (P = 0.02). Remarkably, an age-independent AD effect further reduced the scale-invariant correlations at 1.5-8 h (P = 0.04), leading to the greatest reduction of the scale-invariant correlations in very old people with late-stage AD-resembling closely the loss of correlations at large time scales in SCN-lesioned animals. Thus, aging and AD significantly attenuate the scale invariance of activity fluctuations over multiple time scales. This attenuation may reflect functional changes of the SCN.

Predicting transitory mood from physical activity level among people with severe mental illness in two cultures

BACKGROUND

Previous studies have indicated that physical activity (PA) is positively related to health-related quality of life and well-being among people with severe mental illness (SMI). Physical activity is broadly defined in this research as any skeletal muscle movement resulting in energy expenditure, including common daily activities such as housework and gardening, as well as walking for transportation and formal exercise. Although the physical health benefits of PA are well documented, evidence suggests that PA provides psychological benefits as well.

AIMS

The purpose of this study was to identify if PA level was associated with transitory mood in the everyday lives of people with SMI across two cultures.

METHODS

Subjects were drawn through mental health centres in Serbia (n = 12) and the USA (n = 11). Data were collected using both experience sampling methodology and accelerometry. Data were analyzed using hierarchical linear modelling.

RESULTS

Subjects demonstrated low levels of PA, which did not differ significantly between groups. Hierarchical analysis indicated that PA remained significantly positively associated with mood after accounting for individual variation, and this was consistent across groups.

CONCLUSIONS

This study reinforces previous findings that people with SMI demonstrate low PA levels generally. It also supports the consideration of physical activity interventions as a regular part of psychiatric rehabilitation. It appears that increased PA may have the potential to affect both physical health and mood among people with SMI.

Sleep quality in women with and without postpartum depression

OBJECTIVE

To compare and measure the effects of sleep quality in women with and without postpartum depression.

DESIGN

A case-control repeated measures matched pairs design.

SETTING

Home and obstetric office.

PARTICIPANTS

Forty-six women who were 6 to 26 weeks postpartum. Two participants were dropped from the final analysis because they were outliers.

METHODS

Participants underwent wrist actigraphy at home for 7 consecutive days to measure sleep quality. The Postpartum Depression Screening Scale measured depression severity. Psychosocial variables were collected during a screening interview. A structured clinical interview was used to diagnose postpartum depression. Correlations, t tests, and hierarchical multiple regressions were run to analyze data.

RESULTS

With the exception of wake episodes, sleep latency (B=1.80, SE=0.73, p<.05), wake after sleep onset (B=6.85, SE=2.85, p<.05), and thus sleep efficiency (B=-6.31, SE=3.13, p<.05) predicted postpartum depression symptom severity.

CONCLUSIONS

Women with postpartum depression experienced poorer sleep quality than women without postpartum depression, and sleep quality worsened with increasing postpartum depression symptom severity. Clinicians need to address measures to improve sleep quality in depressed mothers to decrease symptom severity, and researchers need to develop interventions to facilitate better sleep quality in women with postpartum depression.

Heart rate variability and daytime functioning in insomniacs and normal sleepers: preliminary results

OBJECTIVES

This study examined the differences in heart rate variability (HRV) and daytime functioning between insomniacs and normal sleepers.

METHODS

All participants underwent an interview, a medical examination, and a sleep measurement protocol during which they wore an actigraph and logged a sleep diary for a 7-day period to verify their eligibility. Included in the study were 18 insomniacs and 21 normal sleepers. During a laboratory session, these participants completed four paper-pencil tests of sleepiness, anxiety, fatigue, and concentration difficulty and the Wisconsin Card Sorting Test. Resting HRV was recorded under paced breathing.

RESULTS

Neither did insomniacs experience cognitive impairment nor did they experience excessive daytime sleepiness compared with normal sleepers. However, insomniacs experienced higher frequency of fatigue [effect size (ES)=1.14, P=.002] compared with normal sleepers. There was also a trend toward higher trait anxiety score (ES=0.62) and concentration difficulty (ES=0.59) in insomniacs than in normal sleepers. Although a tendency toward lower resting high- frequency (HF) HRV (ES=-0.57) in insomniacs than in normal sleepers was noted, neither the resting low-frequency (LF) HRV nor the LF/HF ratio were different between groups. Subjective sleep estimates correlated to self-reported daytime consequences such as fatigue and concentration difficulty but not cognitive function. On the contrary, objective sleep estimates correlated to problem-solving/conceptualization and learning but not self-reported daytime consequences.

CONCLUSIONS

Insomniacs are not sleepier during the day than normal sleepers. However, they may experience such a daytime symptom as fatigue although cognitive function remains unimpaired.

Circadian activity rhythm abnormalities in ill and recovered bipolar I disorder patients

OBJECTIVES

Most physiological indicators of bipolar disorder (BPD) reflect current acute illness, and rarely have proved to be state-independent. Activity rhythms are highly abnormal in acute phases of BPD; we compared circadian activity rhythms in BPD I patients during ill and recovered states to those of normal controls to test the hypothesis that some abnormalities may persist.

METHODS

We compared 36 adult DSM-IV BPD I patients during acute mania or mixed states, and during full and sustained clinical recovery, to 32 healthy controls of similar age and sex distribution, using wrist-worn, piezoelectric actigraphic monitoring for 72 h and computed cosinor analysis of circadian activity rhythms.

RESULTS

We verified expected major differences between manic or mixed-state BPD I patients and matched normal controls, including phase advances averaging 2.1 h in ill BPD I patients and 1.8 h in recovered patients. Moreover, recovered BPD patients differed highly significantly from controls in several measures, including acrophase advance, higher percentage of nocturnal sleep, and lower average daily activity (mesor). Actigraphic measures among recovered BPD patients were independent of ratings of mania (on the Young Mania Rating Scale), depression (on the Hamilton Depression Rating Scale), or rating-scale scored subjective distress, as well as the type and dose of concurrent psychotropic medication.

CONCLUSIONS

These findings suggest that abnormal activity rhythms, including sustained phase advances, may represent enduring (trait) characteristics of BPD patients even during clinical recovery. If verified, such indices may be useful in supporting diagnoses and as an objective phenotype for genetic or other biological studies.

Comparison of sleep parameters from actigraphy and polysomnography in older women: the SOF study

STUDY OBJECTIVES

Total sleep time (TST), sleep efficiency (SE), and wake after sleep onset (WASO) as assessed by actigraphy gathered in 3 different modes were compared to polysomnography (PSG) measurements. Each mode was compared to PSG to determine which was more accurate. Associations of the difference in TST measurement with demographics and sleep characteristics were examined.

DESIGN

Observational study.

SETTING

Community-based.

PARTICIPANTS

Sixty-eight women (mean age 81.9 years) from the latest visit of the Study of Osteoporotic Fractures who were concurrently measured with PSG and actigraphy.

INTERVENTIONS

N/A.

MEASUREMENTS AND RESULTS

In-home 12-channel PSG was gathered along with actigraphy data in 3 modes: proportional integration mode (PIM), time above threshold (TAT) and zero crossings mode (ZCM). The PIM mode corresponded better to PSG, with a mean overestimation of TST of 17.9 min. For the PIM mode, the estimation of TST and SE by PSG and actigraphy significantly differed (P < 0.01), while the estimation of WASO was similar (P = 0.27). The intraclass correlation between the 2 procedures was moderate to high (PIM mode: TST 0.76; SE 0.61; WASO 0.58). On average, the PIM mode underestimated TST by 68 min for those who slept < or = 5 hr, overestimated TST by 31 min for those with SE < 70%, and underestimated TST by 24 min for self-reported poor sleepers (P < 0.05).

CONCLUSIONS

Sleep parameters from actigraphy corresponded reasonably well to PSG in this population, with the PIM mode of actigraphy correlating highest. Those with poor sleep quality had the largest measurement error between the 2 procedures.

Endogenous circadian rhythm in human motor activity uncoupled from circadian influences on cardiac dynamics

The endogenous circadian pacemaker influences key physiologic functions, such as body temperature and heart rate, and is normally synchronized with the sleep/wake cycle. Epidemiological studies demonstrate a 24-h pattern in adverse cardiovascular events with a peak at approximately 10 a.m. It is unknown whether this pattern in cardiac risk is caused by a day/night pattern of behaviors, including activity level and/or influences from the internal circadian pacemaker. We recently found that a scaling index of cardiac vulnerability has an endogenous circadian peak at the circadian phase corresponding to approximately 10 a.m., which conceivably could contribute to the morning peak in cardiac risk. Here, we test whether this endogenous circadian influence on cardiac dynamics is caused by circadian-mediated changes in motor activity or whether activity and heart rate dynamics are decoupled across the circadian cycle. We analyze high-frequency recordings of motion from young healthy subjects during two complementary protocols that decouple the sleep/wake cycle from the circadian cycle while controlling scheduled behaviors. We find that static activity properties (mean and standard deviation) exhibit significant circadian rhythms with a peak at the circadian phase corresponding to 5-9 p.m. ( approximately 9 h later than the peak in the scale-invariant index of heartbeat fluctuations). In contrast, dynamic characteristics of the temporal scale-invariant organization of activity fluctuations (long-range correlations) do not exhibit a circadian rhythm. These findings suggest that endogenous circadian-mediated activity variations are not responsible for the endogenous circadian rhythm in the scale-invariant structure of heartbeat fluctuations and likely do not contribute to the increase in cardiac risk at approximately 10 a.m.

The suprachiasmatic nucleus functions beyond circadian rhythm generation

We recently discovered that human activity possesses a complex temporal organization characterized by scale-invariant/self-similar fluctuations from seconds to approximately 4 h-(statistical properties of fluctuations remain the same at different time scales). Here, we show that scale-invariant activity patterns are essentially identical in humans and rats, and exist for up to approximately 24 h: six-times longer than previously reported. Theoretically, such scale-invariant patterns can be produced by a neural network of interacting control nodes-system components with feedback loops-operating at different time scales. However such control nodes have not yet been identified in any neurophysiological model of scale invariance/self-similarity in mammals. Here we demonstrate that the endogenous circadian pacemaker (suprachiasmatic nucleus; SCN), known to modulate locomotor activity with a periodicity of approximately 24 h, also acts as a major neural control node responsible for the generation of scale-invariant locomotor patterns over a broad range of time scales from minutes to at least 24 h (rather than solely at approximately 24 h). Remarkably, we found that SCN lesion in rats completely abolished the scale-invariant locomotor patterns between 4 and 24 h and significantly altered the patterns at time scales <4 h. Identification of the control nodes of a neural network responsible for scale invariance is the critical first step in understanding the neurophysiological origin of scale invariance/self-similarity.

Analysis of nighttime activity and daytime pain in patients with chronic back pain using a self-organizing map neural network

There may be a relationship between sleep and pain in patients with chronic back pain. We collected day-time pain and nighttime activity data from 18 patients diagnosed with chronic back pain. The patients were followed for 6 days and 5 nights. Pain levels were collected every 90 min between 0800 hours and 2,200 hours using a computerized electronic diary. Activity levels were collected using a wrist accelerometer (Actiwatch AW-64). The Actiwatch sampled activity counts every 1 min. Patients were asked to wear the Actiwatch on their non-dominant arm. The pain level measurements were interpolated using cubic splines. A mean pain level was calculated for each period 0800 hours to 2,200 hours as well as for the 6-day period. The difference between the mean pain levels for the 6-day period and each 0800 hours to 2,200 hours period was calculated for each patient. Nighttime activity data were analyzed using the Actiwatch Sleep Analysis software. Correlations were calculated between the Actiwatch Sleep Analysis variables and the mean pain level differences for each patient and period. The correlation analysis was performed with SPSS 7.5. We were unable to show any significant relationships.A different approach to analyze the data was used. A Self-Organizing Map (SOM) Neural Network was trained using the original nighttime activity level time series from 10 randomly selected patients. Recall was then performed on all the activity level data. Correlations were calculated between the pain level variance for the 6-day period for each patient and the corresponding difference in the SOM output coordinates. The correlation was found to be r = 0.73, p < 0.01). We conclude that daytime pain levels are not directly correlated with sleep in the following night and that sleep is not directly correlated with daytime pain levels on the following day in this group of patients. There appears to be a correlation between the difference in nighttime activity levels and patterns and the daytime pain variance. Patients who experience large fluctuations in daytime pain levels also show a higher variability in their nighttime activity levels and patterns. Even though we were unable to show a direct relationship between daytime pain and sleep, it may be reasonable to assume that better pain control resulting in less daytime pain fluctuations can provide more stable nighttime activity levels and patterns in this limited group of patients. By using a neural network model, we were able to extract information from the nighttime activity levels even though a traditional statistical analysis was unsuccessful.

Wrist actigraphy in estimation of sleep and wake in intellectually disabled subjects with motor handicaps

BACKGROUND AND PURPOSE

We studied the applicability of wrist actigraphy to sleep-wake estimation in patients with motor handicaps.

PATIENTS AND METHODS

Concomitant polysomnographic and actigraphic recordings (16-24 h) were compared in three groups: normally moving subjects with normal sleep (n=10), sleep-disordered subjects without motor handicaps (n=13) and sleep-disordered patients with different motor disabilities (n=16). The motor abilities of the subjects were determined by clinical evaluation using a grading scale from 0 to 10. Their actual daily activity was calculated from the recordings as average activity scores.

RESULTS

In the healthy subjects, the mean difference between actigraphic and polysomnographic total sleep estimation was negligible (-1 min), while in both sleep-disordered groups, sleep was highly overestimated by actigraphy. There was a significant correlation between the motor ability score and the discrepancy between actigraphy and polysomnography, but individual data points were highly scattered. A more consistent correlation was found between the average activity score/min in actigrams and the discrepancy of actigraphic with polysomnographic total sleep estimation (Spearman's r=-0.58, P=0.0001, n=39). When the recordings with very low average activity score were rejected from the analyses (two patients without and six with motor handicaps), the overestimation of sleep by actigraphy was reduced but it still remained in both sleep-disordered groups. The mean differences of total sleep between actigraphy and polysomnography were 72 and 121 min and the rank order correlation coefficients 0.80 and 0.71 in patients without and with motor handicaps, respectively. The median discrepancy in total sleep estimation was 6% in both sleep-disordered groups.

CONCLUSIONS

In subjects with rudimentary motor abilities, a standard actigraphy can produce a signal, which is related to the amount of sleep scored in polysomnograms. The sleep parameters obtained by the two methods are not equal, however. The inspection of actigrams is more reliable than the clinical scaling of motor abilities in predicting the applicability of wrist actigraphy.

Non-random fluctuations and multi-scale dynamics regulation of human activity

We investigate if known extrinsic and intrinsic factors fully account for the complex features observed in recordings of human activity as measured from forearm motion in subjects undergoing their regular daily routine. We demonstrate that the apparently random forearm motion possesses dynamic patterns characterized by robust scale-invariant and nonlinear features. These patterns remain stable from one subject to another and are unaffected by changes in the average activity level that occur within individual subjects throughout the day and on different days of the week, since they persist during daily routine and when the same subjects undergo time-isolation laboratory experiments designed to account for the circadian phase and to control the known extrinsic factors. Further, by modeling the scheduled events imposed throughout the laboratory protocols, we demonstrate that they cannot account for the observed scaling patterns in activity fluctuations. We attribute these patterns to a previously unrecognized intrinsic nonlinear multi-scale control mechanism of human activity that is independent of known extrinsic factors such as random and scheduled events, as well as the known intrinsic factors which possess a single characteristic time scale such as circadian and ultradian rhythms.

Relationship between power spectra of the awake EEG and psychomotor activity patterns measured by short-term actigraphy

Actigraphy is a quantitative method for the measurement of motor activity. In the present study, actigraphy was used to examine psychomotor correlates of brain activity. Thirty-four psychiatric patients (17 males and 17 females) with different diagnoses participated in this investigation. Directly after EEG recording, motor activity was measured with a wrist actimeter for 15 min in patients in the sitting position. The EEG was quantified by spectrum analysis, and the power spectra as well as other EEG-derived variables were correlated with actigraphic parameters. Occipital and temporoparietal beta1 power was statistically significantly higher in patients with higher activity scores and lower in those with a high density of sleep (SB) or wake bouts (WB). A high density of SB or WB was also positively correlated with higher mean alpha power. Immobile phases measured by actigraphy were positively associated with occipital alpha and with frontal/frontopolar delta activity, preferentially on the side of the left hemisphere. Our results, while preliminary, suggest that short-term actigraphy may be apt to reflect central nervous system arousal.

The role of actigraphy in sleep medicine

During the last decade actigraphy (activity-based monitoring) has become an essential tool in sleep research and sleep medicine. The validity, reliability and limitations of actigraphy for documenting sleep-wake patterns have been addressed. Normative data on sleep-wake patterns across development have been collected. Multiple studies have documented the adequacy of actigraphy to distinguish between clinical groups and to identify certain sleep-wake disorders. Actigraphy has also been shown to be effective in documenting the effects of various behavioral and medical interventions on sleep-wake patterns. Actigraphy is less useful for documenting sleep-wake in individuals who have long motionless periods of wakefulness (e.g. insomnia patients) or who have disorders that involve altered motility patterns (e.g. sleep apnea). Potential users should be aware of a number of pitfalls of actigraphy: (1) validity has not been established for all scoring algorithms or devices, or for all clinical groups; (2) actigraphy is not sufficient for diagnosis of sleep disorders in individuals with motor disorders or high motility during sleep; (3) the use of computer scoring algorithms without controlling for potential artifacts can lead to inaccurate and misleading results.

Sleep detection with an accelerometer actigraph: comparisons with polysomnography

Two validation studies were conducted to optimize the sleep-detection algorithm of the Actillume. The first study used home recordings of postmenopausal women (age range: 51 to 77 years), which were analyzed to derive the optimal algorithm for detecting sleep and wakefulness from wrist activity data, both for nocturnal in-bed recordings and considering the entire 24 h. The second study explored the optimal algorithm to score in-bed recordings of healthy young adults (age range: 19 to 34 years) monitored in the laboratory. In Study I, the algorithm for in-bed recordings (n=39) showed a minute-by-minute agreement of 85% between Actillume and polysomnography (PSG), a correlation of.98, and a mean measurement error (ME) of 21 min for estimates of sleep duration. Using the same algorithm to score 24-h recordings with Webster's rules, an agreement of 89%, a correlation of.90, and 1 min ME were observed. A different algorithm proved optimal to score in-bed recordings (n=31) of young adults, yielding an agreement of 91%, a correlation of.92, and an ME of 5 min. The strong correlations and agreements between sleep estimates from Actillume and PSG in both studies suggest that the Actillume can reliably monitor sleep and wakefulness both in community-residing elderly and healthy young adults in the laboratory. However, different algorithms are optimal for individuals with different characteristics.