Where to place which sensor to measure sedentary behaviour? A method development and comparison among various sensor placements and signal types

Background: Sedentary Behaviour (SB) is associated with several chronic diseases and especially office workers are at increased risk. SB is defined by a sitting or reclined body posture with an energy expenditure ≤1.5 METs. However, current objective methods to measure SB are not consistent with its definition. There is no consensus on which sensor placement and type to be used. Aim: To compare the accuracy of newly developed artificial intelligence models for 15 sensor placements in combination with four signal types (accelerometer only/plus gyroscope and/or magnetometer) to detect posture and physical in-/activity while desk-based activities. Method: Signal features for the model development were extracted from sensor raw data of 30 office workers performing 10 desk-based tasks, each lasting 5 minutes. Direct observation (posture) and indirect calorimetry (in-/activity) served as reference criteria. The best classification model for each sensor was identified and compared among the sensor placements, both using Friedman and post-hoc Wilcoxon tests (p≤0.05). Results: Posture was most accurately measured with a lower body sensor, while in-/activity was most accurately measured with an upper body or waist sensor. The inclusion of additional signal types improved the posture classification for some placements, while the acceleration signal already contained the relevant signal information for the in-/activity classification. Overall, the thigh accelerometer most accurately classified desk-based SB. Conclusion: This study favours, in line with previous work, the measurement of SB with a thigh worn accelerometer, and adds the information that this sensor is also accurate in measuring physical in-/activity while sitting and standing.Swiss National Science FoundationAccepte

Detecting prolonged sitting bouts with the ActiGraph GT3X

The ActiGraph has a high ability to measure physical activity; however, it lacks an accurate posture classification to measure sedentary behavior. The aim of the present study was to develop an ActiGraph (waist-worn, 30 Hz) posture classification to detect prolonged sitting bouts, and to compare the classification to proprietary ActiGraph data. The activPAL, a highly valid posture classification device, served as reference criterion. Both sensors were worn by 38 office workers over a median duration of 9 days. An automated feature selection extracted the relevant signal information for a minute-based posture classification. The machine learning algorithm with optimal feature number to predict the time in prolonged sitting bouts (>= 5 and >= 10 minutes) was searched and compared to the activPAL using Bland-Altman statistics. The comparison included optimized and frequently used cut-points (100 and 150 counts per minute (cpm), with and without low-frequency-extension (LFE) filtering). The new algorithm predicted the time in prolonged sitting bouts most accurate (bias <= 7 minutes/d). Of all proprietary ActiGraph methods, only 150 cpm without LFE predicted the time in prolonged sitting bouts non-significantly different from the activPAL (bias <= 18 minutes/d). However, the frequently used 100 cpm with LFE accurately predicted total sitting time (bias <= 7 minutes/d). To study the health effects of ActiGraph measured prolonged sitting, we recommend using the new algorithm. In case a cut-point is used, we recommend 150 cpm without LFE to measure prolonged sitting and 100 cpm with LFE to measure total sitting time. However, both cpm cut-points are not recommended for a detailed bout analysis.NoneAccepte

Concurrent and discriminant validity of ActiGraph waist and wrist cut-points to measure sedentary behaviour, activity level, and posture in office work

Background: Sedentary Behaviour (SB) gets an increasing attention from ergonomics and public health due to its associated detrimental health effects. A large number of studies record SB with ActiGraph counts-per-minute cut-points, but we still lack valid information about what the cut-points tell us about office work. This study therefore analysed the concurrent and discriminant validity of commonly used cut-points to measure SB, activity level, and posture. Methods: Thirty office workers completed four office tasks at three workplaces (conventional chair, activity-promoting chair, and standing desk) while wearing two ActiGraphs (waist and wrist). Indirect calorimetry and prescribed posture served as reference criteria. Generalized Estimation Equations analysed workplace and task effects on the activity level and counts-per-minute, and kappa statistics and ROC curves analysed the cut-point validity. Results: The activity-promoting chair (p < 0.001, ES ≥ 0.66) but not the standing desk (p = 1.0) increased the activity level, and both these workplaces increased the waist (p ≤ 0.003, ES ≥ 0.63) but not the wrist counts-per-minute (p = 0.74) compared to the conventional chair. The concurrent and discriminant validity was higher for activity level (kappa: 0.52–0.56 and 0.38–0.45, respectively) than for SB and posture (kappa ≤0.35 and ≤ 0.19, respectively). Furthermore, the discriminant validity for activity level was higher for task effects (kappa: 0.42–0.48) than for workplace effects (0.13–0.24). Conclusions: ActiGraph counts-per-minute for waist and wrist placement were – independently of the chosen cut-point – a measure for activity level and not for SB or posture, and the cut-points performed better to detect task effects than workplace effects. Waist cut-points were most valid to measure the activity level in conventional seated office work, but they showed severe limitations for sit-stand desks. None of the placements was valid to detect the increased activity on the activity-promoting chair. Caution should therefore be paid when analysing the effect of workplace interventions on activity level with ActiGraph waist and wrist cut-points

Self-reported and device-measured physical activity in leisure time and at work and associations with cardiovascular events : a prospective study of the physical activity paradox

The beneficial health effects of physical activity, in particular moderate-to-vigorous physical activity (MVPA), are well documented, but there is an ongoing scientific debate whether the domain matters, i.e., whether leisure time physical activity is beneficial and occupational physical activity is detrimental to health, referred to as the physical activity paradox. The present study, therefore, analyzed the association between self-reported and device-measured physical activity and cardiovascular events in both domains. A representative sample of 807 individuals was followed for 14.6 ± 1.1 years, in which 59 cardiovascular events occurred. For self-reported data, Cox proportional hazard models showed no effect of physical activity in leisure and at work, while for device-measured MVPA, beneficial associations with total time spent in MVPA and occupational time spent in MVPA were found, but not for leisure time spent in MVPA. When accounting for both domains in the same model, the associations disappeared. These results indicate that it matters how physical activity is measured and that MVPA is beneficial for cardiovascular health, but the domain in which MVPA occurs does not seem to matter

Exercise-induced neuroplasticity in Parkinson's disease : A metasynthesis of the literature

Parkinson's disease (PD) is a neurodegenerative disorder for which there is currently only symptomatic treatment. During the last decade, there has been an increased interest in investigating physical exercise as a neuroprotective mechanism in PD. Animal studies have suggested that exercise may in fact induce neuroplastic changes, but evidence in humans is still scarce. A handful of reviews have previously reported on exercise-induced neuroplasticity in humans with PD, but few have been systematic, or have mixed studies on both animals and humans, or focused on one neuroplastic outcome only. Here, we provide a systematic review and metasynthesis of the published studies on humans in this research field where we have also included different methods of evaluating neuroplasticity. Our results indicate that various forms of physical exercise may lead to changes in various markers of neuroplasticity. A narrative synthesis suggests that brain function and structure can be altered in a positive direction after an exercise period, whereas a meta-analysis on neurochemical adaptations after exercise points in disparate directions. Finally, a GRADE analysis showed that the current overall level of evidence for exercise-induced neuroplasticity in people with PD is very low. Our results demonstrate that even though the results in this area point in a positive direction, researchers need to provide studies of higher quality using more rigorous methodology

The McMaster Toronto Arthritis patient preference questionnaire (MACTAR): a methodological study of reliability and minimal detectable change after a 6 week-period of acupuncture treatment in patients with rheumatoid arthritis

Abstract Objectives The McMaster Toronto Arthritis patient preference questionnaire (MACTAR) is a semi-structured interview consisting of a baseline and a follow-up interview. The MACTAR baseline is reliable and valid, however the reliability of the MACTAR follow-up is scarcely described. The aim of this study was to describe aspects of reliability and ability to detect changes of the Swedish MACTAR follow-up following acupuncture treatment in individuals with rheumatoid arthritis. Results The study was of Single Subject Experimental Design, with a 2-week non-interventional A-phase and a 6-week intervention B-phase. Eight individuals with RA, age 30–68 years, were included. MACTAR baseline was performed once followed by five assessments with MACTAR follow-up during the A-phase and another ten assessments during the B-phase. Reliability statistics were calculated for measurements 1–3 during the A-phase and the ability to detect effects of acupuncture treatment was tested by celeration lines in the B-phase. The MACTAR follow-up was highly reliable (ICC = 0.7–0.9, SEM = 2.3–4.3, and SDD = 6.2–11.7). Visual and statistical analyses indicated that the MACTAR follow-up could detect effects on individual- and group levels after acupuncture treatment, indicating that the MACTAR follow-up seems to be reliable and is able to detect effects of acupuncture treatment in RA

Detecting prolonged sitting bouts with the ActiGraph GT3X

The ActiGraph has a high ability to measure physical activity; however, it lacks an accurate posture classification to measure sedentary behavior. The aim of the present study was to develop an ActiGraph (waist-worn, 30 Hz) posture classification to detect prolonged sitting bouts, and to compare the classification to proprietary ActiGraph data. The activPAL, a highly valid posture classification device, served as reference criterion. Both sensors were worn by 38 office workers over a median duration of 9 days. An automated feature selection extracted the relevant signal information for a minute-based posture classification. The machine learning algorithm with optimal feature number to predict the time in prolonged sitting bouts (≥5 and ≥10 minutes) was searched and compared to the activPAL using Bland-Altman statistics. The comparison included optimized and frequently used cut-points (100 and 150 counts per minute (cpm), with and without low-frequency-extension (LFE) filtering). The new algorithm predicted the time in prolonged sitting bouts most accurate (bias ≤ 7 minutes/d). Of all proprietary ActiGraph methods, only 150 cpm without LFE predicted the time in prolonged sitting bouts non-significantly different from the activPAL (bias ≤ 18 minutes/d). However, the frequently used 100 cpm with LFE accurately predicted total sitting time (bias ≤ 7 minutes/d). To study the health effects of ActiGraph measured prolonged sitting, we recommend using the new algorithm. In case a cut-point is used, we recommend 150 cpm without LFE to measure prolonged sitting and 100 cpm with LFE to measure total sitting time. However, both cpm cut-points are not recommended for a detailed bout analysis

Is Sitting Always Inactive and Standing Always Active? A Simultaneous Free-Living activPal and ActiGraph Analysis.

Sedentary Behavior (SB), defined as sitting with minimal physical activity, is an emergent public health topic. However, the measurement of SB considers either posture (e.g., activPal) or physical activity (e.g., ActiGraph), and thus neglects either active sitting or inactive standing. The aim of this study was to determine the true amount of active sitting and inactive standing in daily life, and to analyze by how much these behaviors falsify the single sensors' sedentary estimates. Sedentary time of 100 office workers estimated with activPal and ActiGraph was therefore compared with Bland-Altman statistics to a combined sensor analysis, the posture and physical activity index (POPAI). POPAI classified each activPal sitting and standing event into inactive or active using the ActiGraph counts. Participants spent 45.0% [32.2%-59.1%] of the waking hours inactive sitting (equal to SB), 13.7% [7.8%-21.6%] active sitting, and 12.0% [5.7%-24.1%] inactive standing (mean [5th-95th percentile]). The activPal overestimated sedentary time by 30.3% [12.3%-48.4%] and the ActiGraph by 22.5% [3.2%-41.8%] (bias [95% limit-of-agreement]). The results showed that sitting is not always inactive, and standing is not always active. Caution should therefore be paid when interpreting the activPal (ignoring active sitting) and ActiGraph (ignoring inactive standing) measured time as SB.Fysisk aktivitet och hälsosamma hjärnfunktioner bland kontorsarbetare: Delprojekt 1, Tvärsnittsstudi

Somatosensory Focused Balance Training without cues can improve balance and gait in early Parkinson’s disease – a randomised pilot study

<p><b>Purpose:</b> To study the effect of Somatosensory Focused Balance Training without Cues, on gait and balance in people with early Parkinson’s disease.</p> <p><b>Materials and methods:</b> This was a randomised pilot study. Twenty-eight community-dwelling people with early Parkinson’s disease were randomised to immediate or delayed start of a 8w-group training in a community fitness location. Outcomes were measured at preintervention and postintervention. In addition, the early start group performed a 6-month follow up. Clinical outcome measures included: Berg Balance Scale (BBS), BDL Balance Scale, Timed Up and Go, 10 m walk test and the motor part of Unified Parkinson’s disease Rating Scale. Nonparametric statistics was used for analysis.</p> <p><b>Results:</b> Twenty-two participants (10 men, 12 female) were analysed (median age 69, Hoehn & Yahr 2.0). The participants improved significantly in performance of BBS (<i>p</i> = .007), BDL Balance Scale (<i>p</i> = .005), 10 m walk (<i>p</i> = .012) and mUPDRS (<i>p</i> = .027). At follow up, the improvement had declined. The small sample size restricts generalisability of the results.</p> <p><b>Conclusions:</b> The intervention showed positive effects on balance, gait and mUPDRS, suggesting that this specific approach should be further explored as a rehabilitation method to delay balance decline in people in the early stages of Parkinson’s disease.</p

PROGNOSTIC FACTORS FOR IMPROVED PHYSICAL AND EMOTIONAL FUNCTIONING ONE YEAR AFTER INTERDISCIPLINARY REHABILITATION IN PATIENTS WITH CHRONIC PAIN: RESULTS FROM A NATIONAL QUALITY REGISTRY IN SWEDEN

Objective: To investigate prognostic factors for physical and emotional functioning following interdisciplinary multimodal pain rehabilitation, by targeting patients baseline characteristics and health measures. Methods: A prospective cohort of 2,876 patients from 38 specialist clinics across Sweden, who were completing interdisciplinary multimodal pain rehabilitation programmes, was followed through the Swedish Quality Registry for Pain Rehabilitation, from initial assessment to 12-month follow-up. Using logistic regression, baseline data were regressed to predict improvement in Physical functioning and Emotional functioning, derived from principal component analyses of the 36-item Short Form Health Survey (SF-36) and the Hospital Anxiety and Depression Scale (HADS). Results: Employment status emerged as having the largest effect sizes in both Physical functioning and Emotional functioning; Working: odds ratio (OR) 2.05 (95% confidence interval (95% CI) 1.64-2.56) and OR 1.59 (95% CI 1.27-1.98), respectively. Strong beliefs in restored health, better initial emotional health, lower levels of pain and pain interference, and younger age all predicted Physical functioning. European origin, higher levels of general activity, and sense of life control all predicted Emotional functioning. Worse initial physical and emotional health predicted the corresponding dependent outcomes. Conclusion: Employment was consistently found to be an important prognostic factor, suggesting the significance of avoiding delay in interdisciplinary multimodal pain rehabilitation. A positive treatment expectancy was of importance. In general, multidimensional measures indicated that better initial status was more favourable; however, inconsistency implies a complex prognostic picture.Funding Agencies|Swedish Research Council, Stockholm, SwedenSwedish Research Council [2015-02512]; Doctoral School in Health Care Sciences, Karolinska Institutet, Stockholm, Sweden; AFA-Insurance, Stockholm, Sweden [140340]; Research-ALF, County Council of Ostergotland, Linkoping, Sweden [LIO-608021]; Swedish Research Council for Health, Working Life and Welfare (FORTE), Stockholm, Sweden [2017-00177]</p