Barcoding human physical activity to assess chronic pain conditions

Imbalance and Falls in Patients with Parkinson's Disease: Causes and Recent Developments in Training and Sensor-Based Assessment

Imbalance and falls in patients with Parkinson's disease (PD) do not only reduce their quality of life but also their life expectancy. Aging-related symptoms as well as disease-specific motor and non-motor symptoms contribute to these conditions and should be treated when appropriate. In addition to an active lifestyle, advanced exercise training is useful and effective, especially for less medically responsive symptoms such as freezing of gait and postural instability at advanced stages. As treadmill training in non-immersive virtual reality, including dual tasks, significantly reduced the number of falls in PD patients, the mechanism(s) explaining this effect should be further investigated. Such research could help to select the most suitable patients and develop the most effective training protocols based on this novel technology. Real-life digital surrogate markers of mobility, such as those describing aspects of endurance, performance, and the complexity of specific movements, can further improve the quality of mobility assessment using wearables.

Effects of multidisciplinary inpatient rehabilitation on everyday life physical activity and gait in patients with multiple sclerosis

BACKGROUND

Multiple sclerosis is a progressive neurological disease that affects the central nervous system, resulting in various symptoms. Among these, impaired mobility and fatigue stand out as the most prevalent. The progressive worsening of symptoms adversely alters quality of life, social interactions and participation in activities of daily living. The main objective of this study is to bring new insights into the impact of a multidisciplinary inpatient rehabilitation on supervised walking tests, physical activity (PA) behavior and everyday gait patterns.

METHODS

A total of 52 patients, diagnosed with multiple sclerosis, were evaluated before and after 3 weeks of inpatient rehabilitation. Each measurement period consisted of clinical assessments and 7 days home monitoring using foot-mounted sensors. In addition, we considered two subgroups based on the Expanded Disability Status Scale (EDSS) scores: 'mild' (EDSS < 5) and 'severe' (EDSS ≥ 5) disability levels.

RESULTS

Significant improvements in fatigue, quality of life and perceived mobility were reported. In addition, walking capacity, as assessed by the 10-m walking test, two-minute walk test and timed-up-and-go test, improved significantly after rehabilitation. Regarding the home assessment, mildly disabled patients significantly increased their locomotion per day and complexity of daily PA pattern after rehabilitation, while severely disabled patients did not significantly change. There were distinct and significant differences in gait metrics (i.e., gait speed, stride length, cadence) between mildly and severely disabled patients, but the statistical models did not show a significant overall rehabilitation effect on these gait metrics.

CONCLUSION

Inpatient rehabilitation showed beneficial effects on self-reported mobility, self-rated health questionnaires, and walking capacity in both mildly and severely disabled patients. However, these improvements do not necessarily translate to home performance in severely disabled patients, or only marginally in mildly disabled patients. Motivational and behavioral factors should also be considered and incorporated into treatment strategies.

The experiences of people living with obesity and chronic pain: A Qualitative Evidence Synthesis (QES) protocol

INTRODUCTION

There is a substantial and progressive association between chronic pain (CP) and living with overweight or obesity. The relationship between obesity and CP is intricate and complex, with obesity being associated with increased pain-related disability, pain intensity, reduction in physical functioning and poorer psychological well-being. A Qualitative Evidence Synthesis (QES) provides an opportunity to better understand and reveal key areas within the patient experience of these complex interactions to inform best practice and future intervention design.

AIMS

The aim of this QES is to methodically and systematically review and synthesise the qualitative literature reporting on the personal experiences of people who are both living with obesity (PwO) and chronic pain.

METHODS

The phenomenon of interest of this QES is the lived experiences of PwO and CP. The following research question was developed using a modified Population, Intervention, Comparison, Outcome and Study type (PICOS) framework: "What are the lived experiences of people living with obesity and chronic pain?". One review author will conduct a systematic search based on keywords and Medical Subject Headings (MeSH) terms for finding relevant articles in five peer-review databases, from inception to the date of searching. Two review authors will independently apply inclusion and exclusion criteria and screen articles in a two-stage process. The methodological quality of included studies will be assessed using the Critical Appraisal Skills Programme (CASP) tool and data will be extracted using a customised template. We will undertake a thematic synthesis of qualitative data from included studies and report our findings narratively. Confidence in the findings will be assessed based on the Grading of Recommendations Assessment, Development and Evaluation Confidence in Evidence from Reviews of Qualitative Research (GRADE-CER-Qual) approach.

FINDINGS AND DISSEMINATION

This study will follow the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA) and Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ) guidelines. It is anticipated that the findings of the review will facilitate a deep and broad understanding of the complex interactions between CP and obesity and will help inform best practice and future intervention design. Findings will be disseminated through journals that undergo peer review, presentations at conferences, engagement with public and patient advocacy groups, and social media.

ETHICS AND DISSEMINATION

Ethical approval is not required to conduct this review.

TRAIL REGISTRATION

PROSPERO registration number: CRD42023361391.

A robust walking detection algorithm using a single foot-worn inertial sensor: validation in real-life settings

Walking activity and gait parameters are considered among the most relevant mobility-related parameters. Currently, gait assessments have been mainly analyzed in laboratory or hospital settings, which only partially reflect usual performance (i.e., real world behavior). In this study, we aim to validate a robust walking detection algorithm using a single foot-worn inertial measurement unit (IMU) in real-life settings. We used a challenging dataset including 18 individuals performing free-living activities. A multi-sensor wearable system including pressure insoles, multiple IMUs, and infrared distance sensors (INDIP) was used as reference. Accurate walking detection was obtained, with sensitivity and specificity of 98 and 91% respectively. As robust walking detection is needed for ambulatory monitoring to complete the processing pipeline from raw recorded data to walking/mobility outcomes, a validated algorithm would pave the way for assessing patient performance and gait quality in real-world conditions.

Automatic Body Segment and Side Recognition of an Inertial Measurement Unit Sensor during Gait

Inertial measurement unit (IMU) sensors are widely used for motion analysis in sports and rehabilitation. The attachment of IMU sensors to predefined body segments and sides (left/right) is complex, time-consuming, and error-prone. Methods for solving the IMU-2-segment (I2S) pairing work properly only for a limited range of gait speeds or require a similar sensor configuration. Our goal was to propose an algorithm that works over a wide range of gait speeds with different sensor configurations while being robust to footwear type and generalizable to pathologic gait patterns. Eight IMU sensors were attached to both feet, shanks, thighs, sacrum, and trunk, and 12 healthy subjects (training dataset) and 22 patients (test dataset) with medial compartment knee osteoarthritis walked at different speeds with/without insole. First, the mean stride time was estimated and IMU signals were scaled. Using a decision tree, the body segment was recognized, followed by the side of the lower limb sensor. The accuracy and precision of the whole algorithm were 99.7% and 99.0%, respectively, for gait speeds ranging from 0.5 to 2.2 m/s. In conclusion, the proposed algorithm was robust to gait speed and footwear type and can be widely used for different sensor configurations.

Barcoding, linear and nonlinear analysis of full-day leg movements in infants with typical development and infants at risk of developmental disabilities: Cross-sectional study

Traditional methods do not capture the multidimensional domains and dynamic nature of infant behavioral patterns. We aim to compare full-day, in-home leg movement data between infants with typical development (TD) and infants at risk of developmental disabilities (AR) using barcoding and nonlinear analysis. Eleven infants with TD (2-10 months) and nine infants AR (adjusted age: 2-14 months) wore a sensor on each ankle for 7 days. We calculated the standard deviation for linear variability and sample entropy (SampEn) of leg acceleration and angular velocity for nonlinear variability. Movements were also categorized into 16 barcoding states, and we calculated the SampEn and proportions of the barcoding. All variables were compared between the two groups using independent-samples t-test or Mann-Whitney U test. The AR group had larger linear variability compared to the TD group. SampEn was lower in the AR group compared to TD group for both acceleration and angular velocity. Two barcoding states' proportions were significantly different between the two groups. The results showed that nonlinear analysis and barcoding could be used to identify the difference of dynamic multidimensional movement patterns between infants AR and infants with TD. This information may help early diagnosis of developmental disabilities in the future.

Charting everyday activities in later life: Study protocol of the mobility, activity, and social interactions study (MOASIS)

Prominent theories of aging emphasize the importance of resource allocation processes as a means to maintain functional ability, well-being and quality of life. Little is known about which activities and what activity patterns actually characterize the daily lives of healthy older adults in key domains of functioning, including the spatial, physical, social, and cognitive domains. This study aims to gain a comprehensive understanding of daily activities of community-dwelling older adults over an extended period of time and across a diverse range of activity domains, and to examine associations between daily activities, health and well-being at the within- and between-person levels. It also aims to examine contextual correlates of the relations between daily activities, health, and well-being. At its core, this ambulatory assessment (AA) study with a sample of 150 community-dwelling older adults aged 65 to 91 years measured spatial, physical, social, and cognitive activities across 30 days using a custom-built mobile sensor ("uTrail"), including GPS, accelerometer, and audio recording. In addition, during the first 15 days, self-reports of daily activities, psychological correlates, contexts, and cognitive performance in an ambulatory working memory task were assessed 7 times per day using smartphones. Surrounding the ambulatory assessment period, participants completed an initial baseline assessment including a telephone survey, web-based questionnaires, and a laboratory-based cognitive and physical testing session. They also participated in an intermediate laboratory session in the laboratory at half-time of the 30-day ambulatory assessment period, and finally returned to the laboratory for a posttest assessment. In sum, this is the first study which combines multi-domain activity sensing and self-report ambulatory assessment methods to observe daily life activities as indicators of functional ability in healthy older adults unfolding over an extended period (i.e., 1 month). It offers a unique opportunity to describe and understand the diverse individual real-life functional ability profiles characterizing later life.

Associations Between Wearable-Specific Indicators of Physical Activity Behaviour and Insulin Sensitivity and Glycated Haemoglobin in the General Population: Results from the ORISCAV-LUX 2 Study

BACKGROUND

Parameters derived from an acceleration signal, such as the time accumulated in sedentary behaviour or moderate to vigorous physical activity (MVPA), may not be sufficient to describe physical activity (PA) which is a complex behaviour. Incorporating more advanced wearable-specific indicators of PA behaviour (WIPAB) may be useful when characterising PA profiles and investigating associations with health. We investigated the associations of novel objective measures of PA behaviour with glycated haemoglobin (HbA1c) and insulin sensitivity (Quicki index).

METHODS

This observational study included 1026 adults (55% women) aged 18-79y who were recruited from the general population in Luxembourg. Participants provided ≥ 4 valid days of triaxial accelerometry data which was used to derive WIPAB variables related to the activity intensity, accumulation pattern and the temporal correlation and regularity of the acceleration time series.

RESULTS

Adjusted general linear models showed that more time spent in MVPA and a higher average acceleration were both associated with a higher insulin sensitivity. More time accumulated in sedentary behaviour was associated with lower insulin sensitivity. With regard to WIPAB variables, parameters that were indicative of higher PA intensity, including a shallower intensity gradient and higher average accelerations registered during the most active 8 h and 15 min of the day, were associated with higher insulin sensitivity. Results for the power law exponent alpha, and the proportion of daily time accumulated in sedentary bouts > 60 min, indicated that activity which was characterised by long sedentary bouts was associated with lower insulin sensitivity. A greater proportion of time spent in MVPA bouts > 10 min was associated with higher insulin sensitivity. A higher scaling exponent alpha at small time scales (< 90 min), which shows greater correlation in the acceleration time series over short durations, was associated with higher insulin sensitivity. When measured over the entirety of the time series, metrics that reflected a more complex, irregular and unpredictable activity profile, such as the sample entropy, were associated with lower HbA1c levels and higher insulin sensitivity.

CONCLUSION

Our investigation of novel WIPAB variables shows that parameters related to activity intensity, accumulation pattern, temporal correlation and regularity are associated with insulin sensitivity in an adult general population.

Impact of adherence to a lifestyle-integrated programme on physical function and behavioural complexity in young older adults at risk of functional decline: a multicentre RCT secondary analysis

CONTEXT

Long-term adherence to physical activity (PA) interventions is challenging. The Lifestyle-integrated Functional Exercise programmes were adapted Lifestyle-integrated Functional Exercise (aLiFE) to include more challenging activities and a behavioural change framework, and then enhanced Lifestyle-integrated Functional Exercise (eLiFE) to be delivered using smartphones and smartwatches.

OBJECTIVES

To (1) compare adherence measures, (2) identify determinants of adherence and (3) assess the impact on outcome measures of a lifestyle-integrated programme.

DESIGN, SETTING AND PARTICIPANTS

A multicentre, feasibility randomised controlled trial including participants aged 61-70 years conducted in three European cities.

INTERVENTIONS

Six-month trainer-supported aLiFE or eLiFE compared with a control group, which received written PA advice.

OUTCOME MEASURES

Self-reporting adherence per month using a single question and after 6-month intervention using the Exercise Adherence Rating Scale (EARS, score range 6-24). Treatment outcomes included function and disability scores (measured using the Late-Life Function and Disability Index) and sensor-derived physical behaviour complexity measure. Determinants of adherence (EARS score) were identified using linear multivariate analysis. Linear regression estimated the association of adherence on treatment outcome.

RESULTS

We included 120 participants randomised to the intervention groups (aLiFE/eLiFE) (66.3±2.3 years, 53% women). The 106 participants reassessed after 6 months had a mean EARS score of 16.0±5.1. Better adherence was associated with lower number of medications taken, lower depression and lower risk of functional decline. We estimated adherence to significantly increase basic lower extremity function by 1.3 points (p<0.0001), advanced lower extremity function by 1.0 point (p<0.0001) and behavioural complexity by 0.008 per 1.0 point higher EARS score (F(3,91)=3.55, p=0.017) regardless of group allocation.

CONCLUSION

PA adherence was associated with better lower extremity function and physical behavioural complexity. Barriers to adherence should be addressed preintervention to enhance intervention efficacy. Further research is needed to unravel the impact of behaviour change techniques embedded into technology-delivered activity interventions on adherence.

TRIAL REGISTRATION NUMBER

NCT03065088.

Association between chronic pain and physical activity in a Swiss population-based cohort: a cross-sectional study

OBJECTIVE

To assess the bidirectional association between chronic pain and both subjectively and objectively measured physical activity (PA).

DESIGN

Cross-sectional study.

SETTING

Population-based sample in Lausanne, Switzerland, May 2014 to April 2017.

PARTICIPANTS

Non-stratified, representative sample of the population of Lausanne (Switzerland) aged 35-75 years. Participants were excluded if they had missing data for the pain or the PA questionnaires, for accelerometry (defined as >20% of non-wear time or duration <7 days) or for covariates.

PRIMARY OUTCOMES

Primary outcomes were association between chronic pain and previous, subjectively assessed PA (questionnaire), and subsequent, objectively assessed PA (accelerometry). Daily pain, pain duration, number of painful sites and pain intensity were assessed by questionnaire. PA was assessed by questionnaire 2 weeks prior and by accelerometry 2 weeks after completion of the pain questionnaire. PA was further categorised as sedentary (SED), light and moderate-to-vigorous PA.

RESULTS

2598 participants (52.9% women, mean age 60.5 years) had subjectively assessed PA. Multivariable analysis showed time spent in SED to be negatively associated with the number of painful sites: adjusted mean±SE 528±5, 522±7 and 502±7 min/day for 0, 1-2 and 3+ painful sites, respectively, p for trend <0.005. No other association was found between chronic pain and subjectively assessed PA categories. 2205 participants (52.8% women, mean age 61.7 years) had accelerometry-derived PA. No significant association between chronic pain and subsequent objectively assessed PA was found after multivariable analyses.

CONCLUSION

In this Swiss population-based cohort, no consistent association was found between chronic pain and PA. Hence, in the general population, chronic pain does not significantly impact time spent in PA.

Walking and running cadence estimation using a single trunk-fixed accelerometer for daily physical activities assessment

Accurate assessment of the type, duration, and intensity of physical activity (PA) in daily life is considered very important because of the close relationship between PA level, health, and well-being. Therefore, the assessment of PA using lightweight wearable sensors has gained interest in recent years. In particular, the use of activity monitors could help to measure the health-related effects of specific PA interventions. Our study, named as Run4Vit, focuses on evaluating the acute and longterm effects of an eight-week running intervention on PA behaviour and vitality. To achieve this goal, we developed an algorithm to detect running and estimate instantaneous cadence using a single trunk-fixed accelerometer. Cadence was computed using time and frequency domain approaches. Validation was performed over a wide range of locomotion speeds using an open-source gait database. Across all subjects, the cadence estimation algorithms achieved a mean bias and precision of - 0.01 ± 0.69 steps/min for the temporal method and 0.02 ± 1.33 steps/min for the frequency method. The running detection algorithm demonstrated very good performance, with an accuracy of 98% and a precision superior to 99%. These algorithms could be used to extract metrics related to the multiple dimensions of PA, and provide reliable outcome measures for the Run4Vit longitudinal running intervention program. Clinical Relevance- This work aims at validating a multi-dimensional physical activity (PA) classification algorithm for assessing the acute and long-term effects of eight weeks running intervention on PA behaviours and vitality.

Is Complexity of Daily Activity Associated with Physical Function and Life-Space Mobility among Older Adults?

PURPOSE

Information about mobility and physical function may be encoded in the complexity of daily activity pattern. Therefore, daily activity pattern complexity metrics could provide novel insight into the relationship between daily activity behavior and health. The purpose of the present study was to examine the association between the complexity of daily activity behavior and the mobility and physical function among community-dwelling older adults 75, 80, and 85 yr of age.

METHODS

A total of 309 participants wore accelerometers concurrently on the thigh and the trunk for at least three consecutive days. Five activity states (lying, sitting, standing, walking, or activity other than walking) were defined in three different temporal grains (5 s, 1 min, and 5 min), and Lempel-Ziv complexity was evaluated. We assessed complexity of daily activity behavior using the life-space mobility and physical function with distance in preferred pace 6-min walk and the Short Physical Performance Battery.

RESULTS

Weak positive associations were observed between the complexity of daily activity and the mobility and physical function at the finest temporal grains in both sexes (Spearman rho = 0.19 to 0.27, P < 0.05). No significant associations were observed in the coarsest temporal grain in either sex.

CONCLUSIONS

Lempel-Ziv estimates of daily activity complexity with a fine temporal grain seem to be associated with community-dwelling older adults' physical function. The coarsest 5-min temporal grain may have smoothed out physiologically meaningful short activity bouts. Because complexity encodes information related to timing, intensity, and patterning of behavior, complexity of activity could be an informative indicator of future physical function and mobility.

Eigenbehaviour as an Indicator of Cognitive Abilities

With growing use of machine learning algorithms and big data in health applications, digital measures, such as digital biomarkers, have become highly relevant in digital health. In this paper, we focus on one important use case, the long-term continuous monitoring of cognitive ability in older adults. Cognitive ability is a factor both for long-term monitoring of people living alone as well as a relevant outcome in clinical studies. In this work, we propose a new potential digital biomarker for cognitive abilities based on location eigenbehaviour obtained from contactless ambient sensors. Indoor location information obtained from passive infrared sensors is used to build a location matrix covering several weeks of measurement. Based on the eigenvectors of this matrix, the reconstruction error is calculated for various numbers of used eigenvectors. The reconstruction error in turn is used to predict cognitive ability scores collected at baseline, using linear regression. Additionally, classification of normal versus pathological cognition level is performed using a support-vector machine. Prediction performance is strong for high levels of cognitive ability but grows weaker for low levels of cognitive ability. Classification into normal and older adults with mild cognitive impairment, using age and the reconstruction error, shows high discriminative performance with an ROC AUC of 0.94. This is an improvement of 0.08 as compared with a classification with age only. Due to the unobtrusive method of measurement, this potential digital biomarker of cognitive ability can be obtained entirely unobtrusively—it does not impose any patient burden. In conclusion, the usage of the reconstruction error is a strong potential digital biomarker for binary classification and, to a lesser extent, for more detailed prediction of inter-individual differences in cognition.

Advanced analytical methods to assess physical activity behavior using accelerometer time series: A scoping review

Physical activity (PA) is a complex human behavior, which implies that multiple dimensions need to be taken into account in order to reveal a complete picture of the PA behavior profile of an individual. This scoping review aimed to map advanced analytical methods and their summary variables, hereinafter referred to as wearable‐specific indicators of PA behavior (WIPAB), used to assess PA behavior. The strengths and limitations of those indicators as well as potential associations with certain health‐related factors were also investigated. Three databases (MEDLINE, Embase, and Web of Science) were screened for articles published in English between January 2010 and April 2020. Articles, which assessed the PA behavior, gathered objective measures of PA using tri‐axial accelerometers, and investigated WIPAB, were selected. All studies reporting WIPAB in the context of PA monitoring were synthesized and presented in four summary tables: study characteristics, details of the WIPAB, strengths, and limitations, and measures of association between those indicators and health‐related factors. In total, 7247 records were identified, of which 24 articles were included after assessing titles, abstracts, and full texts. Thirteen WIPAB were identified, which can be classified into three different categories specifically focusing on (1) the activity intensity distribution, (2) activity accumulation, and (3) the temporal correlation and regularity of the acceleration signal. Only five of the thirteen WIPAB identified in this review have been used in the literature so far to investigate the relationship between PA behavior and health, while they may provide useful additional information to the conventional PA variables.

Investigating the validity of a single tri-axial accelerometer mounted on the head for monitoring the activities of daily living and the timed-up and go test

BACKGROUND

Quantitative assessments of activities of daily living (ADL) play an essential role in evaluating the impact of disease and interventions on people's quality of life. Motion capture systems traditionally used for quantitative assessments of postural transitions and movement associated with ADL are limited to the laboratory setting. Wearable accelerometers can remove these limitations and enable easier-to-use, longer-term, and remote functional evaluations.

OBJECTIVE

To investigate the validity of a single tri-axial accelerometer mounted on the head for monitoring postural transition and the timed-up-and-go test.

METHODS

Two accelerometers with a sampling frequency of 100 Hz were attached to twelve able-bodied study participants' sternum and right mastoid process. We developed algorithms for the functional calibration of accelerometers and the detection of the postural transitions by measuring the head inclination angle and variations of the gravitational components of the accelerometer readout. Participants performed a battery of ADL tests involving a wide variety of postural transitions. The head-mounted accelerometers results were compared with a sternum-mounted accelerometer and validated against a video motion capture system as a gold standard reference.

RESULTS AND SIGNIFICANCE

The results indicate that, utilizing our proposed algorithm, a single tri-axial accelerometer mounted on the head can deliver high accuracy (>95 %), sensitivity (>90 %), and specificity (100 %) for detecting both postural transitions and walking events. Together with the small size and unobtrusive placement of the head-mounted accelerometer, these results demonstrate an attractive solution for the reliable assessment of ADLs and clinical evaluations based on functional tests such as the timed-up-and-go test.

Longitudinal changes in daily patterns of objectively measured physical activity after falls in older adults with varying degrees of glaucoma

BACKGROUND

Visually impaired older adults have a greater risk of falling, making them particularly susceptible to fall-related health consequences and restricted physical activity. Unclear however, is the relationship between having falls and longitudinal changes in daily patterns of objectively measured physical activity in older adults with visual impairments.

METHODS

We created a three-year prospective cohort study (Falls in Glaucoma Study) of older adults with primary or suspected glaucoma at the Johns Hopkins Wilmer Eye Institute from 2013 to 2015. Cumulative incidence of falls was determined through self-reported fall calendars over 12 months. Participants were then classified into one of three groups: multiple fallers (≥2 falls), single fallers (1 fall), and non-fallers (0). Daily physical activity was measured over 1 week using a waist-bound accelerometer during baseline and three-year follow-ups. Activity fragmentation was defined as the reciprocal of the mean activity bout length, with higher fragmentation reflecting shorter, more fractured bouts of continuous activity. Multivariate linear mixed-effects models were used to assess three-year longitudinal changes in: 1) activity fragmentation, and 2) accumulation of activity across six three-hour intervals from 5 AM to 11 PM.

FINDINGS

In adjusted models accounting for visual field damage and other factors, multiple fallers demonstrated greater annual declines (per year) in daily active bouts (-1.79 bouts/day, 95% confidence interval [CI]: -3.35, -0.22), daily active minutes (-17.15 min/day, 95% CI: -26.35, -7.94), and increased fragmentation (1%, 95% CI: 0, 2%) over the three-year follow-up period as compared to non-fallers; no such changes were seen when comparing single fallers and non-fallers. In time-of-day analyses, multiple fallers experienced greater annual declines in average hourly steps over all periods of the day, though the rate of decline was only significant between 5 PM and 8 PM (-27.07 steps/hour, 95% CI: -51.15, -2.99) compared to non-fallers.

INTERPRETATION

In an older population with visual impairment, multiple falls over 12 months were associated with more transient and fragmented activity over a subsequent three-year period, and activity declines during evening hours, compared to non-fallers. These findings suggest that multiple fallers with visual impairment may be at high risk for a decline in physical capacity and endurance, warranting clinical interventions.

FUNDING

The research was supported in part by National Institutes of Health Grant EY022976.

Clinical value of assessing motor performance in postacute stroke patients

Background

Rehabilitative treatment plans after stroke are based on clinical examinations of functional capacity and patient-reported outcomes. Objective information about daily life performance is usually not available, but it may improve therapy personalization.

Objective

To show that sensor-derived information about daily life performance is clinically valuable for counseling and the planning of rehabilitation programs for individual stroke patients who live at home. Performance information is clinically valuable if it can be used as a decision aid for the therapeutic management or counseling of individual patients.

Methods

This was an observational, cross-sectional case series including 15 ambulatory stroke patients. Motor performance in daily life was assessed with body-worn inertial sensors attached to the wrists, shanks and trunk that estimated basic physical activity and various measures of walking and arm activity in daily life. Stroke severity, motor function and activity, and degree of independence were quantified clinically by standard assessments and patient-reported outcomes. Motor performance was recorded for an average of 5.03 ± 1.1 h on the same day as the clinical assessment. The clinical value of performance information is explored in a narrative style by considering individual patient performance and capacity information.

Results

The patients were aged 59.9 ± 9.8 years (mean ± SD), were 6.5 ± 7.2 years post stroke, and had a National Institutes of Health Stroke Score of 4.0 ± 2.6. Capacity and performance measures showed high variability. There were substantial discrepancies between performance and capacity measures in some patients.

Conclusions

This case series shows that information about motor performance in daily life can be valuable for tailoring rehabilitative therapy plans and counseling according to the needs of individual stroke patients. Although the short recording time (average of 5.03 h) limited the scope of the conclusions, this study highlights the usefulness of objective measures of daily life performance for the planning of rehabilitative therapies. Further research is required to investigate whether information about performance in daily life leads to improved rehabilitative therapy results.

Chronic Pain Diagnosis Using Machine Learning, Questionnaires, and QST: A Sensitivity Experiment

In the last decade, machine learning has been widely used in different fields, especially because of its capacity to work with complex data. With the support of machine learning techniques, different studies have been using data-driven approaches to better understand some syndromes like mild cognitive impairment, Alzheimer’s disease, schizophrenia, and chronic pain. Chronic pain is a complex disease that can recurrently be misdiagnosed due to its comorbidities with other syndromes with which it shares symptoms. Within that context, several studies have been suggesting different machine learning algorithms to classify or predict chronic pain conditions. Those algorithms were fed with a diversity of data types, from self-report data based on questionnaires to the most advanced brain imaging techniques. In this study, we assessed the sensitivity of different algorithms and datasets classifying chronic pain syndromes. Together with this assessment, we highlighted important methodological steps that should be taken into account when an experiment using machine learning is conducted. The best results were obtained by ensemble-based algorithms and the dataset containing the greatest diversity of information, resulting in area under the receiver operating curve (AUC) values of around 0.85. In addition, the performance of the algorithms is strongly related to the hyper-parameters. Thus, a good strategy for hyper-parameter optimization should be used to extract the most from the algorithm. These findings support the notion that machine learning can be a powerful tool to better understand chronic pain conditions.

Relationships of Linear and Non-linear Measurements of Post-stroke Walking Activity and Their Relationship to Weather

Background: Stroke survivors are more sedentary than the general public. Previous research on stroke activity focuses on linear quantities. Non-linear measures, such as Jensen-Shannon Divergence and Lempel-Ziv Complexity, may help explain when and how stroke survivors move so that interventions to increase activity may be designed more effectively.

Objectives: Our objective was to understand what factors affect a stroke survivor's physical activity, including weather, by characterizing activity by step counts, structure, and complexity.

Methods: A custom MATLAB code was used to analyze clinical trial (NCT02835313, https://clinicaltrials.gov/ct2/show/NCT02835313) data presented as minute by minute step counts. Six days of data were analyzed for 142 participants to determine the regularity of activity structure across days and complexity patterns of varied cadences. The effect of steps on structure and complexity, the season's effect on steps, structure, and complexity, and the presence of precipitation's effect on steps and complexity were all analyzed.

Results: Step counts and regularity were linearly related (p < 0.001). Steps and complexity were quadratically related (r² = 0.70 for mean values, 0.64 for daily values). Season affected complexity between spring and winter (p = 0. 019). Season had no effect on steps or structure. Precipitation had no effect on steps or complexity.

Conclusions: Stroke survivors with high step counts are active at similar times each day and have higher activity complexities as measured through patterns of movement at different intensity levels. Non-linear measures, such as Jensen-Shannon Divergence and Lempel-Ziv Complexity, are valuable in describing a person's activity. Weather affects our activity parameters in terms of complexity between spring and winter.

Multidimensional Measures of Physical Activity and Their Association with Gross Motor Capacity in Children and Adolescents with Cerebral Palsy

The current lack of adapted performance metrics leads clinicians to focus on what children with cerebral palsy (CP) do in a clinical setting, despite the ongoing debate on whether capacity (what they do at best) adequately reflects performance (what they do in daily life). Our aim was to measure these children’s habitual physical activity (PA) and gross motor capacity and investigate their relationship. Using five synchronized inertial measurement units (IMU) and algorithms adapted to this population, we computed 22 PA states integrating the type (e.g., sitting, walking, etc.), duration, and intensity of PA. Their temporal sequence was visualized with a PA barcode from which information about pattern complexity and the time spent in each of the six simplified PA states (PAS; considering PA type and duration, but not intensity) was extracted and compared to capacity. Results of 25 children with CP showed no strong association between motor capacity and performance, but a certain level of motor capacity seems to be a prerequisite for the achievement of higher PAS. Our multidimensional performance measurement provides a new method of PA assessment in this population, with an easy-to-understand visual output (barcode) and objective data for clinical and scientific use.

Obesity and pain: a systematic review

BACKGROUND/OBJECTIVES

The current systematic review considered research published within the 10 years preceding June 2019, dealing with the topic of obesity and pain. Within the context of the complex biological and behavioral interrelationships among these phenomena, we sought to identify gaps in the literature and to highlight key targets for future transdisciplinary research. The overarching inclusion criteria were that the included studies could directly contribute to our understanding of these complex phenomena.

METHODS

We searched PubMed/Medline/Cochrane databases dating back 10 years, using the primary search terms "obesity" and "pain," and for a secondary search we used the search terms "pain" and "diet quality."

RESULTS

Included studies (n = 70) are primarily human; however, some animal studies were included to enhance understanding of related basic biological phenomena and/or where human data were absent or significantly limited.

CONCLUSIONS

Our overall conclusions highlight (1) the mechanisms of obesity-related pain (i.e., mechanical, behavioral, and physiological) and potential biological and behavioral contributors (e.g., gender, distribution of body fat, and dietary factors), (2) the requirement for accurate and reliable objective measurement, (3) the need to integrate biological and behavioral contributors into comprehensive, well-controlled prospective study designs.

Using Deep Learning and Resting-State fMRI to Classify Chronic Pain Conditions

Chronic pain is known as a complex disease due to its comorbidities with other symptoms and the lack of effective treatments. As a consequence, chronic pain seems to be under-diagnosed in more than 75% of patients. At the same time, the advance in brain imaging, the popularization of machine learning techniques and the development of new diagnostic tools based on these technologies have shown that these tools could be an option in supporting decision-making of healthcare professionals. In this study, we computed functional brain connectivity using resting-state fMRI data from one hundred and fifty participants to assess the performance of different machine learning models, including deep learning (DL) neural networks in classifying chronic pain patients and pain-free controls. The best result was obtained by training a convolutional neural network fed with data preprocessed using the MSDL probabilistic atlas and using the dynamic time warping (DTW) as connectivity measure. DL models had a better performance compared to other less costly models such as support vector machine (SVM) and RFC, with balanced accuracy ranged from 69 to 86%, while the area under the curve (ROC) ranged from 0.84 to 0.93. Also, DTW overperformed correlation as connectivity measure. These findings support the notion that resting-state fMRI data could be used as a potential biomarker of chronic pain conditions.

From Total Volume to Sequence Maps: Sophisticated Accelerometer Data Analysis

PURPOSE

To date, epidemiological studies have focused on the potential health effects of total volume of physical activity (PA) or sedentary behavior (SB). However, two persons may have the same volume of PA or SB but accumulated in a completely different sequence. The pattern of accumulating PA and SB might be more important for health effects than the total volume. Therefore, the aim was to develop a sophisticated algorithm translating accelerometer data into detailed sequence maps considering how PA and SB are accumulated throughout the day.

METHODS

We developed a novel algorithm to convert accelerometer counts into a sequence map based on behavior states defined by a combination of intensity (SB, light, moderate, and vigorous intensity) and duration (sporadic accumulation or in bouts of different duration). In addition, hierarchical cluster analysis was applied to identify clusters of children with similar behavioral sequence maps.

RESULTS

Clustering resulted in seven clusters of children with similar PA and SB sequence maps: an average cluster (33% of children); a cluster with relatively more SB, light, and moderate PA in bouts (SB and PA bouters, 31%); a cluster characterized by more sporadic SB and light PA (light activity breakers, 26%); and four smaller clusters with 7% of the children or less.

CONCLUSION

This novel algorithm is a next step in more sophisticated analyses of accelerometer data considering how PA and SB are accumulated throughout the day. The next step is identifying whether specific patterns of accumulating PA and SB are associated with improved health outcomes.

Upper limb activity of twenty myoelectric prosthesis users and twenty healthy anatomically intact adults

The upper limb activity of twenty unilateral upper limb myoelectric prosthesis users and twenty anatomically intact adults were recorded over a 7-day period using two wrist worn accelerometers (Actigraph, LLC). This dataset reflects the real-world activities of the participants during their normal day-to-day routines. Participants included students, working adults, and retirees recruited from across the United Kingdom. This dataset offers a potential wealth of knowledge into a poorly understood cohort. The raw unprocessed data files and the activity count data exported from the Actilife software are provided. We also provide a non-wear algorithm developed for the removal of prosthesis non-wear periods and resulting activity count data corresponding to prothesis wear periods. Finally, we have included the transposed activity diaries provided by the participants. Analysis to date has primarily involved assessment of the symmetry of upper limb activity, however, there is potential to undertake additional analysis such as understanding the differences in the way a prosthesis is used compared to an anatomical arm.

Towards a comprehensive set of GPS-based indicators reflecting the multidimensional nature of daily mobility for applications in health and aging research

BACKGROUND

GPS tracking is increasingly used in health and aging research to objectively and unobtrusively assess individuals' daily-life mobility. However, mobility is a complex concept and its thorough description based on GPS-derived mobility indicators remains challenging.

METHODS

With the aim of reflecting the breadth of aspects incorporated in daily mobility, we propose a conceptual framework to classify GPS-derived mobility indicators based on their characteristic and analytical properties for application in health and aging research. In order to demonstrate how the classification framework can be applied, existing mobility indicators as used in existing studies are classified according to the proposed framework. Then, we propose and compute a set of selected mobility indicators based on real-life GPS data of 95 older adults that reflects diverse aspects of individuals' daily mobility. To explore latent dimensions that underlie the mobility indicators, we conduct a factor analysis.

RESULTS

The proposed framework enables a conceptual classification of mobility indicators based on the characteristic and analytical aspects they reflect. Characteristic aspects inform about the content of the mobility indicator and comprise categories related to space, time, movement scope, and attribute. Analytical aspects inform how a mobility indicator is aggregated with respect to temporal scale and statistical property. The proposed categories complement existing studies that often underrepresent mobility indicators involving timing, temporal distributions, and stop-move segmentations of movements. The factor analysis uncovers the following six dimensions required to obtain a comprehensive view of an older adult's daily mobility: extent of life space, quantity of out-of-home activities, time spent in active transport modes, stability of life space, elongation of life space, and timing of mobility.

CONCLUSION

This research advocates incorporating GPS-based mobility indicators that reflect the multi-dimensional nature of individuals' daily mobility in future health- and aging-related research. This will foster a better understanding of what aspects of mobility are key to healthy aging.

Morphine immunomodulation prolongs inflammatory and postoperative pain while the novel analgesic ZH853 accelerates recovery and protects against latent sensitization

Background

Numerous studies have identified the proinflammatory, pronociceptive effects of morphine which ultimately exacerbate pain. Our novel endomorphin analog ZH853 does not produce proinflammatory effects on its own and gives potent, long-lasting analgesia. This study investigates whether ZH853’s lack of interaction with the neuroimmune system reduces the risk of prolonged pain.

Methods

Adult male Sprague-Dawley rats were subjected to one of two treatment paradigms. Either (1) chronic pain followed by chronic treatment with morphine, ZH853 or vehicle, or (2) chronic drug administered prior to pain induction. Complete Freund’s adjuvant (CFA) was injected or paw incision surgery was performed on the left hind plantar foot pad. Drugs were administered through Alzet osmotic minipumps at a rate of 1 μl/h for 5 days at appropriate doses based on prior experiments. Animals were tested for mechanical allodynia and thermal hyperalgesia using von Frey filaments and the Hargreaves apparatus, respectively. Additionally, several gait parameters were measured using the CatWalk XT. When all animals had recovered from pain, 1 mg/kg of naltrexone was administered to test for development of latent sensitization (LS). A second set of animals was used to investigate dorsal horn inflammation following CFA and drug treatment. ANOVAs were used to assess differences between drug treatment groups.

Results

As expected, morphine increased and prolonged pain in all experiments compared to vehicle treatment. However, ZH853 treatment reduced the overall time spent in pain and the severity of pain scores compared to morphine. ZH853 not only reduced inflammation versus morphine treatment but also, in some instances, acted as an anti-inflammatory drug compared to vehicle treatment. Finally, ZH853 prevented the development of LS while vehicle- and morphine-treated animals showed robust relapse to pain.

Conclusions

ZH853 has a favorable side effect profile versus morphine and provides superior analgesia in a number of pain states. We now know that chronic use of this compound reduces time spent in a chronic pain state, the opposite of common opioids like morphine, and reduces the risk of LS, making ZH853 an excellent candidate for clinical development in humans for inflammatory and postoperative pain.

Protocol for the PreventIT feasibility randomised controlled trial of a lifestyle-integrated exercise intervention in young older adults

INTRODUCTION

The European population is rapidly ageing. In order to handle substantial future challenges in the healthcare system, we need to shift focus from treatment towards health promotion. The PreventIT project has adapted the Lifestyle-integrated Exercise (LiFE) programme and developed an intervention for healthy young older adults at risk of accelerated functional decline. The intervention targets balance, muscle strength and physical activity, and is delivered either via a smartphone application (enhanced LiFE, eLiFE) or by use of paper manuals (adapted LiFE, aLiFE).

METHODS AND ANALYSIS

The PreventIT study is a multicentre, three-armed feasibility randomised controlled trial, comparing eLiFE and aLiFE against a control group that receives international guidelines of physical activity. It is performed in three European cities in Norway, Germany, and The Netherlands. The primary objective is to assess the feasibility and usability of the interventions, and to assess changes in daily life function as measured by the Late-Life Function and Disability Instrument scale and a physical behaviour complexity metric. Participants are assessed at baseline, after the 6 months intervention period and at 1 year after randomisation. Men and women between 61 and 70 years of age are randomly drawn from regional registries and respondents screened for risk of functional decline to recruit and randomise 180 participants (60 participants per study arm).

ETHICS AND DISSEMINATION

Ethical approval was received at all three trial sites. Baseline results are intended to be published by late 2018, with final study findings expected in early 2019. Subgroup and further in-depth analyses will subsequently be published.

TRIAL REGISTRATION NUMBER

NCT03065088; Pre-results.

Spatiotemporal gait analysis of older persons in clinical practice and research : Which parameters are relevant?

For older persons walking is a basic activity of daily life which characterizes the person's functional mobility. Therefore, the improvement of walking performance is a major clinical outcome during geriatric rehabilitation. Furthermore, walking performance is relevant for several geriatric research issues. Quantitative gait analysis can describe walking performance in detail. Besides gait speed, various qualitative parameters related to different aspects of walking performance, such as symmetry, regularity, coordination, dynamic balance and foot movement during the swing phase, can serve as outcome parameters in geriatric research and in clinical practice. Clinicians and researchers have to decide which parameters are appropriate to be used as relevant outcome parameters in the investigated person or group of persons.

EEG Multiscale Complexity in Schizophrenia During Picture Naming

Introduction: Patients with schizophrenia show cognitive deficits that are evident both behaviourally and with EEG recordings. Recent studies have suggested that non-linear analyses of EEG might more adequately reflect the complex, irregular, non-stationary behavior of neural processes than more traditional ERP measures. Non-linear analyses have been mainly applied to EEGs from patients at rest, whereas differences in complexity might be more evident during task performance.

Objective: We aimed to investigate changes in non-linear brain dynamics of patients with schizophrenia during cognitive processing.

Method: 18 patients and 17 matched healthy controls were asked to name pictures. EEG data were collected at rest and while they were performing a naming task. EEGs were analyzed with the classical Lempel-Ziv Complexity (LZC) and with the Multiscale LZC. Electrodes were grouped in seven regions of interest (ROI).

Results: As expected, controls had fewer naming errors than patients. Regarding EEG complexity, the interaction between Group, Task and ROI indicated that patients showed higher complexity values in right frontal regions only at rest, where no differences in complexity between patients and controls were found during the naming task. EEG complexity increased from rest to task in controls in left temporal-parietal regions, while no changes from rest to task were observed in patients. Finally, differences in complexity between patients and controls depended on the frequency bands: higher values of complexity in patients at rest were only observed in fast bands, indicating greater heterogeneity in patients in local dynamics of neuronal assemblies.

Conclusion: Consistent with previous studies, schizophrenic patients showed higher complexity than controls in frontal regions at rest. Interestingly, we found different modulations of brain complexity during a simple cognitive task between patients and controls. These data can be interpreted as indicating schizophrenia-related failures to adapt brain functioning to the task, which is reflected in poorer behavioral performance.

Concern about Falling and Complexity of Free-Living Physical Activity Patterns in Well-Functioning Older Adults

BACKGROUND

Fall-related psychological concerns are common among older adults, potentially contributing to functional decline as well as to restriction of activities and social participation. To effectively prevent such negative consequences, it is important to understand how even very low concern about falling could affect physical activity behavior in everyday life. We hypothesized that concern about falling is associated with a reduction in diversity, dynamics, and performance of daily activities, and that these features can be comprehensively quantified in terms of complexity of physical activity patterns.

METHODS

A sample of 40 community-dwelling older adults were assessed for concern about falling using the Falls Efficacy Scale-International (FES-I). Free-living physical activity was assessed using a set of metrics derived from data recorded with a chest-worn tri-axial accelerometer. The devised metrics characterized physical activity behavior in terms of endurance (total locomotion time, longest locomotion period, usual walking cadence), performance (cadence of longest locomotion period, locomotion periods with at least 30 steps and 100 steps/min), and complexity of physical activity patterns. Complexity was quantified according to variations in type, intensity, and duration of activities, and was considered as an adaptive response to environmental exigencies over the course of the day.

RESULTS

Based on FES-I score, participants were classified into two groups: not concerned at all/fully confident (n = 25) and concerned/less confident (n = 15). Demographic and health-related variables did not differ significantly between groups. Comparison of physical activity behavior indicated no significant differences for endurance-related metrics. In contrast, performance and complexity metrics were significantly lower in the less confident group compared to the fully confident group. Among all metrics, complexity of physical activity patterns appeared as the most discriminative feature between fully confident and less confident participants (p = 0.001, non-parametric Cliff's delta effect size = 0.63).

CONCLUSIONS

These results extend our understanding of the interplay between low concern about falling and physical activity behavior of community-dwelling older persons in their everyday life context. This information could serve to better design and evaluate personalized intervention programs in future prospective studies.

Complexity of Daily Physical Activity Is More Sensitive Than Conventional Metrics to Assess Functional Change in Younger Older Adults

The emerging mHealth applications, incorporating wearable sensors, enables continuous monitoring of physical activity (PA). This study aimed at analyzing the relevance of a multivariate complexity metric in assessment of functional change in younger older adults. Thirty individuals (60–70 years old) participated in a 4-week home-based exercise intervention. The Community Balance and Mobility Scale (CBMS) was used for clinical assessment of the participants’ functional balance and mobility performance pre- and post- intervention. Accelerometers worn on the low back were used to register PA of one week before and in the third week of the intervention. Changes in conventional univariate PA metrics (percentage of walking and sedentary time, step counts, mean cadence) and complexity were compared to the change as measured by the CBMS. Statistical analyses (21 participants) showed significant rank correlation between the change as measured by complexity and CBMS (ρ = 0.47, p = 0.03). Smoothing the activity output improved the correlation (ρ = 0.58, p = 0.01). In contrast, change in univariate PA metrics did not show correlations. These findings demonstrate the high potential of the complexity metric being useful and more sensitive than conventional PA metrics for assessing functional changes in younger older adults.

Wearable Sensors and the Assessment of Frailty among Vulnerable Older Adults: An Observational Cohort Study

Background: The geriatric syndrome of frailty is one of the greatest challenges facing the U.S. aging population. Frailty in older adults is associated with higher adverse outcomes, such as mortality and hospitalization. Identifying precise early indicators of pre-frailty and measures of specific frailty components are of key importance to enable targeted interventions and remediation. We hypothesize that sensor-derived parameters, measured by a pendant accelerometer device in the home setting, are sensitive to identifying pre-frailty. Methods: Using the Fried frailty phenotype criteria, 153 community-dwelling, ambulatory older adults were classified as pre-frail (51%), frail (22%), or non-frail (27%). A pendant sensor was used to monitor the at home physical activity, using a chest acceleration over 48 h. An algorithm was developed to quantify physical activity pattern (PAP), physical activity behavior (PAB), and sleep quality parameters. Statistically significant parameters were selected to discriminate the pre-frail from frail and non-frail adults. Results: The stepping parameters, walking parameters, PAB parameters (sedentary and moderate-to-vigorous activity), and the combined parameters reached and area under the curve of 0.87, 0.85, 0.85, and 0.88, respectively, for identifying pre-frail adults. No sleep parameters discriminated the pre-frail from the rest of the adults. Conclusions: This study demonstrates that a pendant sensor can identify pre-frailty via daily home monitoring. These findings may open new opportunities in order to remotely measure and track frailty via telehealth technologies.

What is the Best Configuration of Wearable Sensors to Measure Spatiotemporal Gait Parameters in Children with Cerebral Palsy?

Wearable inertial devices have recently been used to evaluate spatiotemporal parameters of gait in daily life situations. Given the heterogeneity of gait patterns in children with cerebral palsy (CP), the sensor placement and analysis algorithm may influence the validity of the results. This study aimed at comparing the spatiotemporal measurement performances of three wearable configurations defined by different sensor positioning on the lower limbs: (1) shanks and thighs, (2) shanks, and (3) feet. The three configurations were selected based on their potential to be used in daily life for children with CP and typically developing (TD) controls. For each configuration, dedicated gait analysis algorithms were used to detect gait events and compute spatiotemporal parameters. Fifteen children with CP and 11 TD controls were included. Accuracy, precision, and agreement of the three configurations were determined in comparison with an optoelectronic system as a reference. The three configurations were comparable for the evaluation of TD children and children with a low level of disability (CP-GMFCS I) whereas the shank-and-thigh-based configuration was more robust regarding children with a higher level of disability (CP-GMFCS II–III).

Behavioural activation by mental health nurses for late-life depression in primary care: a randomized controlled trial

BACKGROUND

Depressive symptoms are common in older adults. The effectiveness of pharmacological treatments and the availability of psychological treatments in primary care are limited. A behavioural approach to depression treatment might be beneficial to many older adults but such care is still largely unavailable. Behavioural Activation (BA) protocols are less complicated and more easy to train than other psychological therapies, making them very suitable for delivery by less specialised therapists. The recent introduction of the mental health nurse in primary care centres in the Netherlands has created major opportunities for improving the accessibility of psychological treatments for late-life depression in primary care. BA may thus address the needs of older patients while improving treatment outcome and lowering costs.The primary objective of this study is to compare the effectiveness and cost-effectiveness of BA in comparison with treatment as usual (TAU) for late-life depression in Dutch primary care. A secondary goal is to explore several potential mechanisms of change, as well as predictors and moderators of treatment outcome of BA for late-life depression.

METHODS/DESIGN

Cluster-randomised controlled multicentre trial with two parallel groups: a) behavioural activation, and b) treatment as usual, conducted in primary care centres with a follow-up of 52 weeks. The main inclusion criterion is a PHQ-9 score > 9. Patients are excluded from the trial in case of severe mental illness that requires specialized treatment, high suicide risk, drug and/or alcohol abuse, prior psychotherapy, change in dosage or type of prescribed antidepressants in the previous 12 weeks, or moderate to severe cognitive impairment. The intervention consists of 8 weekly 30-min BA sessions delivered by a trained mental health nurse.

DISCUSSION

We expect BA to be an effective and cost-effective treatment for late-life depression compared to TAU. BA delivered by mental health nurses could increase the availability and accessibility of non-pharmacological treatments for late-life depression in primary care.

TRIAL REGISTRATION

This study is retrospectively registered in the Dutch Clinical Trial Register NTR6013 on August 25th 2016.

A wrist sensor and algorithm to determine instantaneous walking cadence and speed in daily life walking

In daily life, a person's gait-an important marker for his/her health status-is usually assessed using inertial sensors fixed to lower limbs or trunk. Such sensor locations are not well suited for continuous and long duration measurements. A better location would be the wrist but with the drawback of the presence of perturbative movements independent of walking. The aim of this study was to devise and validate an algorithm able to accurately estimate walking cadence and speed for daily life walking in various environments based on acceleration measured at the wrist. To this end, a cadence likelihood measure was designed, automatically filtering out perturbative movements and amplifying the periodic wrist movement characteristic of walking. Speed was estimated using a piecewise linear model. The algorithm was validated for outdoor walking in various and challenging environments (e.g., trail, uphill, downhill). Cadence and speed were successfully estimated for all conditions. Overall median (interquartile range) relative errors were -0.13% (-1.72 2.04%) for instantaneous cadence and -0.67% (-6.52 6.23%) for instantaneous speed. The performance was comparable to existing algorithms for trunk- or lower limb-fixed sensors. The algorithm's low complexity would also allow a real-time implementation in a watch.

Monitoring and Promoting Old Age Health Stabilization in Real Life

Abstract. Research on aging in different domains largely focuses on age-related decrements or intervention-related improvements, often in controlled laboratory conditions or with psychometric tests of maximum ability or traits. This special issue on monitoring and promoting old-age health stabilization in real life focuses on the short-term and long-term age-related stabilization and maintenance in diverse psychological areas, including well-being, self-esteem, subjective health, and social interactions. One central focus in all studies is the clear focus on behaviors in real-life contexts. The papers both review and present ways in which new technologies and research approaches can provide novel opportunities for monitoring and promoting the stabilization of various aspects of health and quality of life in the daily lives of healthy older adults.

Quantifying dimensions of physical behavior in chronic pain conditions

Background

Chronic pain, defined as persistent or recurrent pain lasting longer than 3 months, is a frequent condition affecting an important percent of population worldwide. Pain chronicity can be caused by many different factors and is a frequent component of many neurological disorders. An important aspect for clinical assessment and design of effective treatment and/or rehabilitation strategies is to better understand the impact of pain on domains of functioning in everyday life. The aim of this study was to identify the objectively quantifiable features of physical functioning in daily life and to evaluate their effectiveness to differentiate behavior among subjects with different pain conditions.

Method

Body worn sensors were used to record movement data during five consecutive days in 92 subjects. Sensor data were processed to characterize the physical behavior in terms of type, intensity, duration and temporal pattern of activities, postures and movements performed by subjects in daily life. Metrics quantifying these features were subsequently used to devise composite scores using a factor analysis approach. The severity of clinical condition was assessed using a rating of usual pain intensity on a 10-cm visual analog scale. The relationship between pain intensity and the estimated metrics/composite scores was assessed using multiple regression and discriminant analysis.

Results

According to the factor analysis solution, two composite scores were identified, one integrating the metrics quantifying the amount and duration of activity periods, and the other the metrics quantifying complexity of temporal patterns, i.e., the diversity of body movements and activities, and the manner in which they are organized throughout time. All estimated metrics and composite scores were significantly different between groups of subjects with clinically different pain levels. Moreover, analysis revealed that pain intensity seemed to have a more significant impact on the overall physical behavior, as it was quantified by a global composite score, whereas the type of chronic pain appeared to influence mostly the complexity of the temporal pattern.

Conclusion

The methodology described could be informative for the design of objective outcome measures in chronic pain management/rehabilitation programs.

Physical Behavior in Older Persons during Daily Life: Insights from Instrumented Shoes

Activity level and gait parameters during daily life are important indicators for clinicians because they can provide critical insights into modifications of mobility and function over time. Wearable activity monitoring has been gaining momentum in daily life health assessment. Consequently, this study seeks to validate an algorithm for the classification of daily life activities and to provide a detailed gait analysis in older adults. A system consisting of an inertial sensor combined with a pressure sensing insole has been developed. Using an algorithm that we previously validated during a semi structured protocol, activities in 10 healthy elderly participants were recorded and compared to a wearable reference system over a 4 h recording period at home. Detailed gait parameters were calculated from inertial sensors. Dynamics of physical behavior were characterized using barcodes that express the measure of behavioral complexity. Activity classification based on the algorithm led to a 93% accuracy in classifying basic activities of daily life, i.e., sitting, standing, and walking. Gait analysis emphasizes the importance of metrics such as foot clearance in daily life assessment. Results also underline that measures of physical behavior and gait performance are complementary, especially since gait parameters were not correlated to complexity. Participants gave positive feedback regarding the use of the instrumented shoes. These results extend previous observations in showing the concurrent validity of the instrumented shoes compared to a body-worn reference system for daily-life physical behavior monitoring in older adults.

Differences between work and leisure in temporal patterns of objectively measured physical activity among blue-collar workers

Background

Leisure time physical activity (LTPA) is generally associated with favorable cardiovascular health outcomes, while occupational physical activity (OPA) shows less clear, or even opposite, cardiovascular effects. This apparent paradox is not sufficiently understood, but differences in temporal patterns of OPA and LTPA have been suggested as one explanation. Our aim was to investigate the extent to which work and leisure (non-occupational time) differ in temporal activity patterns among blue-collar workers, and to assess the modification of these patterns by age and gender.

Methods

This study was conducted on a cross-sectional sample of male (n = 108) and female (n = 83) blue-collar workers, aged between 21 and 65 years. Physical activity and sedentary behavior were assessed using accelerometers (Actigraph GT3X+) worn on the thigh and trunk for four consecutive days. Temporal patterns of OPA and LTPA were retrieved using Exposure Variation Analysis (EVA), and expressed in terms of percentage of work and leisure time spent in uninterrupted periods of different durations (<1 min, 1–5 min, 5–10 min, 10–30 min, 30–60 min and > 60 min) of sitting, standing, and walking. Repeated measures ANOVA and linear regression analyses were used to test a) possible differences between OPA and LTPA in selected EVA derivatives, and b) the modification of these differences by age and gender.

Results

OPA showed a larger percentage time walking in brief (<5 min) periods [mean (SD): 33.4 % (12.2)], and less time in prolonged (>30 min) sitting [7.0 % (9.3)] than LTPA [walking 15.4 % (5.0); sitting 31.9 % (15.3)], even after adjustment for the difference between work and leisure in total time spent in each activity type. These marked differences in the temporal pattern of OPA and LTPA were modified by gender, but not age.

Conclusion

We found that the temporal patterns of OPA and LTPA among blue-collar workers were markedly different even after adjustment for total physical activity time, and that this difference was modified by gender. We recommend using EVA derivatives in future studies striving to disentangle the apparent paradoxical cardiovascular effect of physical activity at work and during leisure.

A randomized controlled trial of custom foot orthoses for the treatment of plantar heel pain

BACKGROUND

Up to 10% of people will experience heel pain. The purpose of this prospective, double-blind, randomized clinical trial was to compare custom foot orthoses (CFO), prefabricated foot orthoses (PFO), and sham insole treatment for plantar fasciitis.

METHODS

Seventy-seven patients with plantar fasciitis for less than 1 year were included. Outcome measures included first step and end of day pain, Revised Foot Function Index short form (FFI-R), 36-Item Short Form Health Survey (SF-36), activity monitoring, balance, and gait analysis.

RESULTS

The CFO group had significantly improved total FFI-R scores (77.4 versus 57.2; P = .03) without group differences for FFI-R pain, SF-36, and morning or evening pain. The PFO and CFO groups reported significantly lower morning and evening pain. For activity, the CFO group demonstrated significantly longer episodes of walking over the sham (P = .019) and PFO (P = .03) groups, with a 125% increase for CFOs, 22% PFOs, and 0.2% sham. Postural transition duration (P = .02) and balance (P = .05) improved for the CFO group. There were no gait differences. The CFO group reported significantly less stretching and ice use at 3 months.

CONCLUSIONS

The CFO group demonstrated 5.6-fold greater improvements in spontaneous physical activity versus the PFO and sham groups. All three groups improved in morning pain after treatment that included standardized athletic shoes, stretching, and ice. The CFO changes may have been moderated by decreased stretching and ice use after 3 months. These findings suggest that more objective measures, such as spontaneous physical activity improvement, may be more sensitive and specific for detecting improved weightbearing function than traditional clinical outcome measures, such as pain and disease-specific quality of life.

Unraveling dynamics of human physical activity patterns in chronic pain conditions

Chronic pain is a complex disabling experience that negatively affects the cognitive, affective and physical functions as well as behavior. Although the interaction between chronic pain and physical functioning is a well-accepted paradigm in clinical research, the understanding of how pain affects individuals' daily life behavior remains a challenging task. Here we develop a methodological framework allowing to objectively document disruptive pain related interferences on real-life physical activity. The results reveal that meaningful information is contained in the temporal dynamics of activity patterns and an analytical model based on the theory of bivariate point processes can be used to describe physical activity behavior. The model parameters capture the dynamic interdependence between periods and events and determine a ‘signature’ of activity pattern. The study is likely to contribute to the clinical understanding of complex pain/disease-related behaviors and establish a unified mathematical framework to quantify the complex dynamics of various human activities.

Recommendations for standardizing validation procedures assessing physical activity of older persons by monitoring body postures and movements

Physical activity is an important determinant of health and well-being in older persons and contributes to their social participation and quality of life. Hence, assessment tools are needed to study this physical activity in free-living conditions. Wearable motion sensing technology is used to assess physical activity. However, there is a lack of harmonisation of validation protocols and applied statistics, which make it hard to compare available and future studies. Therefore, the aim of this paper is to formulate recommendations for assessing the validity of sensor-based activity monitoring in older persons with focus on the measurement of body postures and movements. Validation studies of body-worn devices providing parameters on body postures and movements were identified and summarized and an extensive inter-active process between authors resulted in recommendations about: information on the assessed persons, the technical system, and the analysis of relevant parameters of physical activity, based on a standardized and semi-structured protocol. The recommended protocols can be regarded as a first attempt to standardize validity studies in the area of monitoring physical activity.

Hypertension prevalence and diminished blood pressure-related hypoalgesia in individuals reporting chronic pain in a general population: the Tromsø study

Resting blood pressure (BP) is inversely related to pain sensitivity in individuals free of chronic pain, reflecting homeostatic interactions between cardiovascular and pain modulatory systems. Several laboratory studies indicate that BP-related hypoalgesia is diminished in chronic pain patients, suggesting dysfunction in these interacting systems. Separate epidemiological findings reveal elevated hypertension prevalence in the chronic pain population. This study for the first time simultaneously evaluated both hypertension prevalence and BP-related hypoalgesia as they relate to chronic pain in the same sample. Resting BP and pain sensitivity were evaluated in a large general population sample (n=10,135, aged 30-87years). Subjects participated in a standardized 106s cold pressor test, providing pain ratings at 9s intervals. Self-reported presence of chronic pain and history of hypertension and use of antihypertensive medication were assessed. Significant interactions between chronic pain status and resting systolic (P<.001) and diastolic BP (P<.001) on mean pain ratings were observed. These interactions were due to significant (P<.001) BP-related hypoalgesia in individuals free of chronic pain that was twice the magnitude of the hypoalgesia observed in the group reporting chronic pain. Presence of chronic pain was associated with significantly increased odds of comorbid hypertension (P<.001). Within the chronic pain group, higher chronic pain intensity was a significant predictor of positive hypertension status beyond the effects of traditional demographic risk factors (P<.05). Results are consistent with the hypothesis that increased hypertension risk in the chronic pain population might be linked in part to chronic pain-related dysfunction in interacting cardiovascular-pain modulatory systems.