Preliminary field validity of ActiGraph-based energy expenditure estimation in wheelchair users with spinal cord injury.

STUDY DESIGN: Cross-sectional validation study. OBJECTIVES: To develop a raw acceleration signal-based random forest (RF) model for predicting total energy expenditure (TEE) in manual wheelchair users (MWUs) and evaluate the preliminary field validity of this new model, along with four existing models published in prior literature, using the Doubly Labeled Water (DLW) method. SETTING: General community and research institution in Pittsburgh, USA. METHODS: A total of 78 participants' data from two previous studies were used to develop the new RF model. A seven-day cross-sectional study was conducted to collect participants' free-living physical activity and TEE data, resting metabolic rate, demographics, and anthropometrics. Ten MWUs with spinal cord injury (SCI) completed the study, with seven participants having valid data for evaluating the preliminary field validity of the five models. RESULTS: The RF model achieved a mean absolute error (MAE) of 0.59 ± 0.60 kcal/min and a mean absolute percentage error (MAPE) of 23.6% ± 24.3% on the validation set. For preliminary field validation, the five assessed models yielded MAE from 136 kcal/day to 1141 kcal/day and MAPE from 6.1% to 50.2%. The model developed by Nightingale et al. in 2015 achieved the best performance (MAE: 136 ± 96 kcal/day, MAPE: 6.1% ± 4.7%), while the RF model achieved comparable performance (MAE: 167 ± 99 kcal/day, MAPE: 7.4% ± 5.1%). CONCLUSIONS: Two existing models and our newly developed RF model showed good preliminary field validity for assessing TEE in MWUs with SCI and the potential to detect lifestyle change in this population. Future large-scale field validation studies and model iteration are recommended.

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

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

A catalog of validity indices for step counting wearable technologies during treadmill walking: the CADENCE-Kids study.

BACKGROUND: Wearable technologies play an important role in measuring physical activity (PA) and promoting health. Standardized validation indices (i.e., accuracy, bias, and precision) compare performance of step counting wearable technologies in young people. PURPOSE: To produce a catalog of validity indices for step counting wearable technologies assessed during different treadmill speeds (slow [0.8-3.2 km/h], normal [4.0-6.4 km/h], fast [7.2-8.0 km/h]), wear locations (waist, wrist/arm, thigh, and ankle), and age groups (children, 6-12 years; adolescents, 13-17 years; young adults, 18-20 years). METHODS: One hundred seventeen individuals (13.1 ± 4.2 years, 50.4% female) participated in this cross-sectional study and completed 5-min treadmill bouts (0.8 km/h to 8.0 km/h) while wearing eight devices (Waist: Actical, ActiGraph GT3X+, NL-1000, SW-200; Wrist: ActiGraph GT3X+; Arm: SenseWear; Thigh: activPAL; Ankle: StepWatch). Directly observed steps served as the criterion measure. Accuracy (mean absolute percentage error, MAPE), bias (mean percentage error, MPE), and precision (correlation coefficient, r; standard deviation, SD; coefficient of variation, CoV) were computed. RESULTS: Five of the eight tested wearable technologies (i.e., Actical, waist-worn ActiGraph GT3X+, activPAL, StepWatch, and SW-200) performed at < 5% MAPE over the range of normal speeds. More generally, waist (MAPE = 4%), thigh (4%) and ankle (5%) locations displayed higher accuracy than the wrist location (23%) at normal speeds. On average, all wearable technologies displayed the lowest accuracy across slow speeds (MAPE = 50.1 ± 35.5%), and the highest accuracy across normal speeds (MAPE = 15.9 ± 21.7%). Speed and wear location had a significant effect on accuracy and bias (P < 0.001), but not on precision (P > 0.05). Age did not have any effect (P > 0.05). CONCLUSIONS: Standardized validation indices focused on accuracy, bias, and precision were cataloged by speed, wear location, and age group to serve as important reference points when selecting and/or evaluating device performance in young people moving forward. Reduced performance can be expected at very slow walking speeds (0.8 to 3.2 km/h) for all devices. Ankle-worn and thigh-worn devices demonstrated the highest accuracy. Speed and wear location had a significant effect on accuracy and bias, but not precision. TRIAL REGISTRATION: Clinicaltrials.gov NCT01989104 . Registered November 14, 2013.

The feasibility and reliability of actigraphy to monitor sleep in intensive care patients: an observational study.

BACKGROUND: Sleep amongst intensive care patients is reduced and highly fragmented which may adversely impact on recovery. The current challenge for Intensive Care clinicians is identifying feasible and accurate assessments of sleep that can be widely implemented. The objective of this study was to investigate the feasibility and reliability of a minimally invasive sleep monitoring technique compared to the gold standard, polysomnography, for sleep monitoring. METHODS: Prospective observational study employing a within subject design in adult patients admitted to an Intensive Care Unit. Sleep monitoring was undertaken amongst minimally sedated patients via concurrent polysomnography and actigraphy monitoring over a 24-h duration to assess agreement between the two methods; total sleep time and wake time. RESULTS: We recruited 80 patients who were mechanically ventilated (24%) and non-ventilated (76%) within the intensive care unit. Sleep was found to be highly fragmented, composed of numerous sleep bouts and characterized by abnormal sleep architecture. Actigraphy was found to have a moderate level of overall agreement in identifying sleep and wake states with polysomnography (69.4%; K = 0.386, p < 0.05) in an epoch by epoch analysis, with a moderate level of sensitivity (65.5%) and specificity (76.1%). Monitoring accuracy via actigraphy was improved amongst non-ventilated patients (specificity 83.7%; sensitivity 56.7%). Actigraphy was found to have a moderate correlation with polysomnography reported total sleep time (r = 0.359, p < 0.05) and wakefulness (r = 0.371, p < 0.05). Bland-Altman plots indicated that sleep was underestimated by actigraphy, with wakeful states overestimated. CONCLUSIONS: Actigraphy was easy and safe to use, provided moderate level of agreement with polysomnography in distinguishing between sleep and wakeful states, and may be a reasonable alternative to measure sleep in intensive care patients. Clinical Trial Registration number ACTRN12615000945527 (Registered 9/9/2015).

Agreement analysis of sleep patterns between self-reported questionnaires and actigraphy in adults.

PURPOSE: To investigate the agreement in sleep pattern recording by self-reported sleep questionnaires and actigraphy in adults. METHODS: This is a cross-sectional study. Men and women who met inclusion criteria were recruited for this study. The inclusion criteria were apparently healthy Omani nationals ages 19 to 50 years. Sleep questionnaires were randomly distributed in Muscat either directly or via electronic and paper announcements. Data were collected from the participants using the self-reported questionnaires with four piloted questions for sleep pattern identification and through the actigraphy wristband given to subjects to wear for a week. Cohen's kappa test was performed for agreement analysis. RESULTS: A total of 964 Omani subjects between ages 18 and 59 years of both genders were recruited and completed the questionnaires successfully. Out of these, only 321 subjects wore the actigraphy wristband for 1 week (response rate = 33%). Agreement analysis reported a mild level of agreement for the monophasic (41%), moderate level for biphasic (59%), and good level for polyphasic (70%) sleep patterns. The overall agreement level of sleep patterns between the two methods was 57%. There is a low specificity of self-reported assessment in reporting sleep pattern. CONCLUSION: The average agreement level of subjective versus objective assessments of sleep patterns was moderate at 57% and self-reported sleep pattern is not specific. The study recommends the use of actigraphy along with sleep questionnaires for accurate assessment of sleep patterns in cohort studies.

Proof of principle study: diagnostic accuracy of a novel algorithm for the estimation of sleep stages and disease severity in patients with sleep-disordered breathing based on actigraphy and respiratory inductance plethysmography.

PURPOSE: In this proof of principle study, we evaluated the diagnostic accuracy of the novel Nox BodySleepTM 1.0 algorithm (Nox Medical, Iceland) for the estimation of disease severity and sleep stages based on features extracted from actigraphy and respiratory inductance plethysmography (RIP) belts. Validation was performed against in-lab polysomnography (PSG) in patients with sleep-disordered breathing (SDB). METHODS: Patients received PSG according to AASM. Sleep stages were manually scored using the AASM criteria and the recording was evaluated by the novel algorithm. The results were analyzed by descriptive statistics methods (IBM SPSS Statistics 25.0). RESULTS: We found a strong Pearson correlation (r=0.91) with a bias of 0.2/h for AHI estimation as well as a good correlation (r=0.81) and an overestimation of 14 min for total sleep time (TST). Sleep efficiency (SE) was also valued with a good Pearson correlation (r=0.73) and an overestimation of 2.1%. Wake epochs were estimated with a sensitivity of 0.65 and a specificity of 0.59 while REM and non-REM (NREM) phases were evaluated a sensitivity of 0.72 and 0.74, respectively. Specificity was 0.74 for NREM and 0.68 for REM. Additionally, a Cohen's kappa of 0.62 was found for this 3-class classification problem. CONCLUSION: The algorithm shows a moderate diagnostic accuracy for the estimation of sleep. In addition, the algorithm determines the AHI with good agreement with the manual scoring and it shows good diagnostic accuracy in estimating wake-sleep transition. The presented algorithm seems to be an appropriate tool to increase the diagnostic accuracy of portable monitoring. The validated diagnostic algorithm promises a more appropriate and cost-effective method if integrated in out-of-center (OOC) testing of patients with suspicion for SDB.

Reliability of ActiGraph GT3X+ placement location in the estimation of energy expenditure during moderate and high-intensity physical activities in young and older adults.

WHO defines physical activity (PA) as any bodily movement produced by skeletal muscles that requires energy expenditure (EE). The purpose of this study was to compare the EE estimations by ActiGraph GT3X+ with a gold standard measurement, the portable gas analyser in a set of 3 different PAs. This cross-sectional study involved 56 participants, age range (years, [min, max]: young people [20, 33], older adults [65, 83]). Participants completed a single session of three experimental PAs including biking, treadmill walking, and treadmill running. Each participant wore five GT3X+ triaxial accelerometers and a portable gas analyser used as the gold standard measurement. The GT3X+ were placed on the wrists, the waist (centred at the pelvis), and the ankles. ActiGraph GT3X+ and MetaMax3B records were investigated through intraclass correlation coefficient. Magnitude of measurement error was estimated using Effect Size. The GT3X+ wrist and GT3X+ waist underestimated EE regardless of the PA type. The GT3X+ ankles strongly overestimated EE during biking (mean bias = 489 ± 392%) and walking (mean bias = 106 ± 58%), while it underestimated EE during running (mean bias = -47 ± 27%). The ActiGraph GT3X+ does not provide accurate EE estimates across a range of placement locations during moderate and high-intensity PA.

Validity of self-reported and objectively measured sedentary behavior in pregnancy.

BACKGROUND: Sedentary behavior (SED) is a potential risk factor for poor pregnancy outcomes. We evaluated the validity of several common and one new method to assess SED across three trimesters of pregnancy. METHODS: This cohort study of pregnant women measured objective and self-reported SED each trimester via thigh-worn activPAL3 micro (criterion), waist-worn Actigraph GT3X, and self-report from the Pregnancy Physical Activity Questionnaire (PPAQ) and the de novo Sedentary Behavior Two Domain Questionnaire (SB2D). SED (hours per day) and percent time in SED (SED%) from activPAL were compared to GT3X, SB2D, and PPAQ using Pearson's r, ICC, Bland-Altman analysis, and comparison of criterion SED and SED% across tertiles of alternative methods. RESULTS: Fifty-eight women (mean age 31.5 ± 4.8 years; pre-pregnancy BMI 25.1 ± 5.6 kg/m2; 76% white) provided three trimesters of valid activPAL data. Compared to activPAL, GT3X had agreement ranging from r = 0.54-0.66 and ICC = 0.52-0.65. Bland-Altman plots revealed small mean differences and unpatterned errors, but wide limits of agreement (greater than ±2 h and ± 15%). The SB2D and PPAQ had r < 0.5 and ICC < 0.3 vs. activPAL SED, with lower agreement during the 2nd and 3rd trimesters, and performed poorly in Bland-Altman analyses. SED% from the modified SB2D performed best of the self-reported instruments with modest mean differences, r ranging from 0.55 to 0.60, and ICCs from 0.31-0.33; though, limits of agreement were greater than ±35%. Significant trends in activPAL SED were observed across increasing tertiles of SB2D SED in the 1st and 3rd trimesters (both p ≤ 0.001), but not the 2nd trimester (p = 0.425); and for PPAQ SED in the 1st and 2nd trimesters (both p < 0.05), but not the 3rd trimester (p = 0.158). AcitvPAL SED and SED% increased significantly across tertiles of GT3X SED and SED% as well as SB2D SED% (all p-for-trend ≤ 0.001). CONCLUSIONS: Compared to activPAL, waist-worn GT3X produced moderate agreement, though similar mean estimates of SED across pregnancy. Self-report questionnaires had large absolute error and wide limits of agreement for SED hr./day; SB2D measurement of SED% was the best self-report method. These data suggest activPAL be used to measure SED when possible, followed by GT3X, and - when necessary - SB2D assessing SED% in pregnancy. TRIAL REGISTRATION: www.clinicaltrials.gov NCT03084302 on 3/20/2017.

Construct Validity of the Chilean-Spanish Version of the Functional Status Score for the Intensive Care Unit: A Prospective Observational Study Using Actigraphy in Mechanically Ventilated Patients.

OBJECTIVE: To evaluate the construct validity (hypotheses testing) of the Chilean-Spanish version of the Functional Status Score for the Intensive Care Unit (FSS-ICU) using continuous actigraphy from intensive care unit (ICU) admission to ICU discharge. DESIGN: The Chilean-Spanish version of the FSS-ICU was used in a prospective observational study to mainly evaluate its correlation with actigraphy variables. The FSS-ICU was assessed on awakening and at ICU discharge, while actigraphy variables were recorded from ICU admission to ICU discharge. SETTING: A 12-bed academic medical-surgical ICU. PARTICIPANTS: Mechanically ventilated patients (N=30), of 92 patients screened. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Construct validity of the FSS-ICU Chilean-Spanish version was assessed by testing 12 hypotheses, including the correlation with activity counts, activity time (>99 counts/min), inactivity time (0-99 counts/min), muscle strength, ICU length of stay, and duration of mechanical ventilation. RESULTS: The median FSS-ICU was 19 points (interquartile range [IQR], 10-26 points) on awakening and 28.5 points (IQR, 22-32 points) at ICU discharge. There was no floor/ceiling effect of the FSS-ICU at awakening (0%/0%) and only a ceiling effect at ICU discharge that was acceptable (0%/10%). Less activity time was associated with better mobility on the FSS-ICU at both awakening (ρ=-0.62, P<.001) and ICU discharge (ρ=-0.79, P<.001). Activity counts and activity time were not correlated as expected with the FSS-ICU. CONCLUSIONS: The Chilean-Spanish FSS-ICU had a strong correlation with inactivity time during the ICU stay. These findings enhance the available clinimetric properties of the FSS-ICU.

Measurement of sedentary time and physical activity in rheumatoid arthritis: an ActiGraph and activPAL™ validation study.

Accurate measurement of sedentary time and physical activity (PA) is essential to establish their relationships with rheumatoid arthritis (RA) outcomes. Study objectives were to: (1) validate the GT3X+ and activPAL3µ™, and develop RA-specific accelerometer (count-based) cut-points for measuring sedentary time, light-intensity PA and moderate-intensity PA (laboratory-validation); (2) determine the accuracy of the RA-specific (vs. non-RA) cut-points, for estimating free-living sedentary time in RA (field-validation). Laboratory-validation: RA patients (n = 22) were fitted with a GT3X+, activPAL3µ™ and indirect calorimeter. Whilst being video-recorded, participants undertook 11 activities, comprising sedentary, light-intensity and moderate-intensity behaviours. Criterion standards for devices were indirect calorimetry (GT3X+) and direct observation (activPAL3µ™). Field-validation: RA patients (n = 100) wore a GT3X+ and activPAL3µ™ for 7 days. The criterion standard for sedentary time cut-points (RA-specific vs. non-RA) was the activPAL3µ™. Results of the laboratory-validation: GT3X-receiver operating characteristic curves generated RA-specific cut-points (counts/min) for: sedentary time = ≤ 244; light-intensity PA = 245-2501; moderate-intensity PA ≥ 2502 (all sensitivity ≥ 0.87 and 1-specificity ≤ 0.11). ActivPAL3µ™-Bland-Altman 95% limits of agreement (lower-upper [min]) were: sedentary = (- 0.1 to 0.2); standing = (- 0.7 to 1.1); stepping = (- 1.2 to 0.6). Results of the field-validation: compared to the activPAL3µ™, Bland-Altman 95% limits of agreement (lower-upper) for sedentary time (min/day) estimated by the RA-specific cut-point = (- 42.6 to 318.0) vs. the non-RA cut-point = (- 19.6 to 432.0). In conclusion, the activPAL3µ™ accurately quantifies sedentary, standing and stepping time in RA. The RA-specific cut-points offer a validated measure of sedentary time, light-intensity PA and moderate-intensity PA in these patients, and demonstrated superior accuracy for estimating free-living sedentary time, compared to non-RA cut-points.

Comparative validity of energy expenditure prediction algorithms using wearable devices for people with spinal cord injury.

STUDY DESIGN: Cross-sectional validation study. OBJECTIVES: To conduct a literature search for existing energy expenditure (EE) predictive algorithms using ActiGraph activity monitors for manual wheelchairs users (MWUs) with spinal cord injury (SCI), and evaluate their validity using an out-of-sample dataset. SETTING: Research institution in Pittsburgh, USA. METHODS: A literature search resulted in five articles containing five sets of predictive equations using an ActiGraph activity monitor for MWUs with SCI. Out-of-sample data were collected from 29 MWUs with chronic SCI who were asked to follow an activity protocol while wearing an ActiGraph GT9X Link on the dominant wrist. They also wore a portable metabolic cart which provided the criterion measure for EE. The out-of-sample dataset was used to evaluate the validity of the five sets of EE predictive equations. RESULTS: None of the five sets of predictive equations demonstrated equivalence within 20% of the criterion measure based on an equivalence test. The mean absolute error for the five sets of predictive equations ranged from 0.87 to 6.41 kilocalories per minute (kcal min-1) when compared with the criterion measure, and the intraclass correlation estimates ranged from 0.06 to 0.59. The range between the Bland-Altman upper and lower limits of agreement was from 4.70 kcal min-1 to 25.09 kcal min-1. CONCLUSIONS: The existing EE predictive equations based on ActiGraph monitors for MWUs with SCI showed varied performance when compared with the criterion measure. Their accuracies may not be sufficient to support future clinical and research use. More work is needed to develop more accurate EE predictive equations for this population.

The Use of Wearable Technology to Objectively Measure Sleep Quality and Physical Activity Among Pregnant Women in Urban Lima, Peru: A Pilot Feasibility Study.

INTRODUCTION: Sleep quality and physical activity can affect the mental and physical health of pregnant women and their babies in utero. METHODS: We investigated the feasibility of objectively assessing sleep quality and physical activity among resource-constrained, pregnant women in urban Lima, Peru. Twenty pregnant women were asked to complete written sleep logs and wear ActiSleep, a wristwatch-like device that records sleep quality (consecutive minutes of uninterrupted sleep) and physical activity (steps), for seven consecutive days. Sociodemographic data and pregnancy characteristics were also collected. RESULTS: Of twenty women, 13 (65%) had sufficient data collected for analysis. The mean age of study participants was 26.3 years (SD = 3.9), with a mean sleep duration of 6.9 h (SD = 1.4). The median time for sleep onset was 21:15. The mean time for sleep latency was 17.3 min; and wake after sleep onset was 116 min. The mean number of awakenings was 20.4 (SD = 6.7); and sleep efficiency was 77.9%. For physical activity, participants averaged of 6,029 steps per day (SD = 3,087). DISCUSSION: Objective assessment of sleep quality and physical activity among pregnant women in a resource-constrained setting was promising, despite modest data collection completeness. Wearable technology could be used in health interventions to improve sleep quality and physical activity among this population.

Reactivity to accelerometer measurement of youth with moderate and severe intellectual disabilities.

BACKGROUND: Reactivity occurs when research participants alter their behaviours due to the awareness of being monitored, which is a concern with using wearable devices to measure physical activity. The purpose of this study was to examine reactivity to accelerometer measurement among youth with moderate and severe intellectual disabilities (ID). METHODS: A sample of 175 youth with ID (108 with moderate and 67 with severe ID) was recruited from residential centres in China. Demographic data were measured using a parent-reported questionnaire, and light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA) were measured using the ActiGraph GT3X accelerometers. Data were analysed using an analysis of covariances where Day 1 LPA/MVPA, Day 2-6 LPA/MVPA, and Day 7 LPA/MVPA were repeated measures. RESULTS: Youth with moderate ID had significantly higher LPA (8.01%) and MVPA (10.30%) on Day 1 than Day 2-6. Similarly, youth with severe ID had significantly higher LPA (21.69%) and MVPA (19.48%) on Day 1 than Day 2-6. An inverse reactivity was also found on Day 7 among youth with severe ID for LPA (-10.65%) and MVPA (-14.82%). CONCLUSIONS: Reactivity to accelerometer measurement was found for youth with moderate and severe ID. Findings support the utilisation of a 1-day familiarisation period, as well as discounting the final day of measurement, when examining physical activity behaviours among youth with moderate and severe ID.

Use of Actigraphy to Measure Symptoms of Agitation in Dementia.

OBJECTIVE: To evaluate the feasibility and validity of actigraphy as a measurement of agitation in dementia. METHODS: Participants aged 65 and older, diagnosed with dementia, residing in a geriatric psychiatry inpatient unit or long-term care facility were included in a cross-sectional study. Agitation was assessed using the Cohen-Mansfield Agitation Inventory (CMAI) and the Neuropsychiatric Inventory (NPI). Actigraphy was measured over seven days and compared across groups categorized as low or high agitation based on a CMAI cutoff score of 50. RESULTS: Twenty participants were enrolled (mean age = 74.3 years, standard deviation [SD] = 8.69). The 24-hour mean motor activity as measured with actigraphy was significantly different between the low and high agitation groups (180.23, SD = 86.34 versus 81.51, SD = 30.29, Z = 2.29; p = 0.02). Most actigraph variables had significant correlations with CMAI and NPI scores. CONCLUSION: Actigraphy was highly correlated with informant-based methods for measuring agitation in individuals with dementia and actigraphy may be useful tool for measuring agitation.

Which actigraphic variables optimally characterize the sleep-wake cycle of individuals with bipolar disorders?

OBJECTIVE: To examine which combination of objectively measured actigraphy parameters best characterizes the sleep-wake cycle of euthymic individuals with bipolar disorder (BD) compared with healthy controls (HC). METHODS: Sixty-one BD cases and 61 matched HC undertook 21 consecutive days of actigraphy. Groups were compared using discriminant function analyses (DFA) that explored dimensions derived from mean values of sleep parameters (Model 1); variability of sleep parameters (2); daytime activity (3); and combined sleep and activity parameters (4). Exploratory within-group analyses examined characteristics associated with misclassification. RESULTS: After controlling for depressive symptoms, the combined model (4) correctly classified 75% cases, while the sleep models (1 and 2) correctly classified 87% controls. The area under the curve favored the combined model (0.86). Age was significantly associated with misclassification among HC, while a diagnosis of BD-II was associated with an increased risk of misclassifications of cases. CONCLUSION: Including sleep variability and activity parameters alongside measures of sleep quantity improves the characterization of cases of euthymic BD and helps distinguish them from HC. If replicated, the findings indicate that traditional approaches to actigraphy (examining mean values for the standard set of sleep parameters) may represent a suboptimal approach to understanding sleep-wake cycles in BD.

Step-counting accuracy of activity monitors in persons with Down syndrome.

BACKGROUND: Accelerometers and pedometers have been used to monitor the number of steps. However, the evidence on the step-counting accuracy of these devices - especially accelerometers - is limited in persons with Down syndrome (DS). This study therefore examined the accuracy of accelerometers placed on the hip or wrist and of a pedometer with a uni-axial accelerometer mechanism in measuring steps in persons with DS and whether device error is associated with walking speed, height, weight, body mass index, waist circumference, leg length, age or sex. METHOD: Seventeen persons with DS (eight women and nine men; age 33 ± 15 years) walked over-ground for 6 min at their preferred speed. The steps were measured with a hip-worn and a wrist-worn ActiGraph accelerometer using the manufacturer's default (DF) and low-frequency extension (LFE) filters, and with the NL-1000 New Lifestyles pedometer on the hip. Steps were also measured with hand tally which served as the criterion. RESULTS: Absolute percent error was considerable and differed statistically between devices (P = 0.001); however, error improved for accelerometers when LFE was applied (Hip-DF: 31.6 ± 18.8%; Hip-LFE: 9.7 ± 12.8%; Wrist-DF: 32.7 ± 14.2%; Wrist-LFE: 13.6 ± 10.2%; Pedometer: 23.2 ± 22.8%). Bland-Altman plots indicated underestimation of steps for accelerometers and the pedometer. Application of LFE, however, improved the prediction of the accelerometers. The number of steps measured by the hip accelerometer with LFE and by the pedometer did not differ statistically from actual steps. Steps by the remaining methods were significantly lower than hand tally (P ≤ 0.001). Correlations between percent error for each device and walking speed, anthropometry, age or sex ranged between -0.28 and +0.48, and were non-significant, except for age. CONCLUSIONS: The results demonstrated that the pedometer and ActiGraph accelerometers have considerable error in measuring steps of persons with DS. Application of LFE, however, significantly improved the step-counting performance of the Actigraph accelerometers.

Evaluation of wrist and hip sedentary behaviour and moderate-to-vigorous physical activity raw acceleration cutpoints in older adults.

Wrist-based accelerometers are now common in assessing physical activity (PA) and sedentary behaviour (SB) in population-based studies, but there is a scarcity of raw acceleration cutpoints in older adults. The study aimed to determine and evaluate wrist-based GENEActiv (GA) and hip-based ActiGraph GT3X+ (AG) raw acceleration cutpoints for SB and moderate-to-vigorous PA (MVPA) in older adults ≥60 years of age. A laboratory-based calibration analyses of 34 healthy older adults involved receiver operator characteristic (ROC) curves to determine raw acceleration cutpoints for SB and MVPA. ROC analysis revealed an area under the curve (AUC) of 0.88 for GA SB and MVPA, and 0.90 for AG SB and 0.94 for AG MVPA. Sensitivity optimised SB and specificity optimised MVPA GA cutpoints of 57 mg and 104 mg, and AG cutpoints of 15 mg and 69 mg were also generated, respectively. Cross-validation analysis revealed moderate agreement for GA and AG SB cutpoints, and fair to substantial agreement for GA and AG MVPA cutpoints, respectively. The resultant cutpoints can classify older adults as engaging in SB or not engaging in MVPA but the sensitivity optimised SB cutpoints should be interpreted with a degree of caution due to their modest cross-validation results.

Does Spinal Cord Stimulation Really Influence Sleep?

BACKGROUND: To date, clinical pain research has typically used subjective questionnaires to assess effectiveness of treatment. However, in the near future, new technologies may provide us objective outcome measures as an alternative to self-report. The goal of this study is to compare subjective and objective sleep assessments in a population of failed back surgery syndrome (FBSS) patients, treated with spinal cord stimulation (SCS). METHODS: Twenty-two patients diagnosed with FBSS received SCS. Sleep data was collected at three time point: prior to SCS implantation (B), one month after SCS (T1), and two months after SCS (T2). Sleep data measured by actigraphy provided objective sleep data and were compared to Pittsburgh sleep quality index (PSQI) scores. Agreement between sleep parameters, total sleep time (TST), sleep efficiency (SE), and sleep onset latency (SOL), was examined. RESULTS: Nineteen out of 22 patients completed the study. We identified significant differences between objective and subjective measurements for TST and SE at baseline and after two months of SCS, with patients underestimating both parameters on the PSQI in comparison to objective measurements. For SOL no significant differences were found, although patients subjectively overestimated SOL at B. CONCLUSION: The results about sleep measurements shown in this population of chronic pain patients, suggest that the subjective ratings scored worse than the objective measurements. Second, short-term SCS mainly seems to affect subjectively measured sleep parameters, especially SOL. This study shows the discrepancies between objective and subjective assessments in chronic pain research. Objective tools are indispensable for a correct assessment and treatment of sleep parameters. They are also playing a role as a biofeedback tool and are supporting the rehabilitation process.

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.

Convergent validity of actigraphy with polysomnography and parent reports when measuring sleep in children with Down syndrome.

BACKGROUND: There is a need for rigorous measures of sleep in children with Down syndrome as sleep is a substantial problem in this population and there are barriers to obtaining the gold standard polysomnography (PSG). PSG is cost-prohibitive when measuring treatment effects in some clinical trials, and children with Down syndrome may not cooperate with undergoing a PSG. Minimal information is available on the validity of alternative methods of assessing sleep in children with Down syndrome, such as actigraphy and parent ratings. Our study examined the concurrent and convergent validity of different measures of sleep, including PSG, actigraphy and parent reports of sleep among children with Down syndrome. METHOD: A clinic (n = 27) and a community (n = 47) sample of children with Down syndrome were examined. In clinic, children with Down syndrome wore an actigraph watch during a routine PSG. In the community, children with Down syndrome wore an actigraph watch for a week at home at night as part of a larger study on sleep and behaviour. Their parent completed ratings of the child's sleep during that same week. RESULTS: Actigraph watches demonstrated convergent validity with PSG when measuring a child with Down syndrome's total amount of sleep time, total wake time after sleep onset and sleep period efficiency. In contrast, actigraph watches demonstrated poor correlations with parent reports of sleep, and with PSG when measuring the total time in bed and total wake episodes. Actigraphy, PSG and parent ratings of sleep demonstrated poor concurrent validity with clinical diagnosis of obstructive sleep apnoea. CONCLUSION: Our current data suggest that actigraph watches demonstrate convergent validity and are sensitive to measuring certain sleep constructs (duration, efficiency) in children with Down syndrome. However, parent reports, such as the Children's Sleep Habits Questionnaire, may be measuring other sleep constructs. These findings highlight the importance of selecting measures of sleep related to target concerns.