Quantification of free-living activity patterns using accelerometry in adults with mental illness

Seeking safety: Movement dynamics after post-contact immobility

Post-contact immobility (PCI) is a final attempt to avoid predation. Here, for the first time, we examine the pattern of movement and immobility when antlion larvae resume activity after PCI. To simulate contact with, and escape from, a predator we dropped the larvae onto three different substrates: Paper, Shallow sand (2.3mm-deep) and Deep sand (4.6mm-deep). The Paper lining a Petri dish represented a hard surface that antlion larvae could not penetrate to hide. The Shallow sand permitted the antlions to dig but not to submerge completely whereas the Deep sand allowed them both to dig and to submerge. We tracked their paths automatically and recorded alternating immobility and movement durations over 90min. On the impenetrable substrate, antlion larvae showed super-diffusive dispersal, their movement durations became longer, their immobility durations became shorter and their instantaneous speeds increased. This is consistent with the antlions needing to leave an area of hard substrate and quickly to find somewhere to hide. On Shallow sand, antlion larvae exhibited a modest increase in movement duration, a modest decrease in immobility duration and a concomitant diffusive dispersal. This is consistent with their use of a spiral search, presumably for a suitable depth of sand, to conceal themselves. On Deep sand, the movement and immobility durations of the antlion larvae did not change and their dispersal was sub-diffusive because they were able to bury themselves. On Paper, the distribution of immobility durations had a long tail, consistent with a log-normal distribution. On Shallow and Deep sand, most of the distribution was fitted better by a power law or a log-normal. Our results suggest that PCI in antlion larvae is a disruptive event and that post-PCI movement and immobility gradually return to the pattern typical of intermittent locomotion, depending on the scope for burying and hiding in the substrate.

General spectral characteristics of human activity and its inherent scale-free fluctuations

The scale-free nature of daily human activity has been observed in different aspects; however, the description of its spectral characteristics is incomplete. General findings are complicated by the fact that-although actigraphy is commonly used in many research areas-the activity calculation methods are not standardized; therefore, activity signals can be different. The presence of 1/f noise in activity or acceleration signals was mostly analysed for short time windows, and the complete spectral characteristic has only been examined in the case of certain types of them. To explore the general spectral nature of human activity in greater detail, we have performed Power Spectral Density (PSD) based examination and Detrended Fluctuation Analysis (DFA) on several-day-long, triaxial actigraphic acceleration signals of 42 healthy, free-living individuals. We generated different types of activity signals from these, using different acceleration preprocessing techniques and activity metrics. We revealed that the spectra of different types of activity signals generally follow a universal characteristic including 1/f noise over frequencies above the circadian rhythmicity. Moreover, we discovered that the PSD of the raw acceleration signal has the same characteristic. Our findings prove that the spectral scale-free nature is generally inherent to the motor activity of healthy, free-living humans, and is not limited to any particular activity calculation method.

TWO-SAMPLE TESTS FOR MULTIVARIATE REPEATED MEASUREMENTS OF HISTOGRAM OBJECTS WITH APPLICATIONS TO WEARABLE DEVICE DATA

Repeated observations have become increasingly common in biomedical research and longitudinal studies. For instance, wearable sensor devices are deployed to continuously track physiological and biological signals from each individual over multiple days. It remains of great interest to appropriately evaluate how the daily distribution of biosignals might differ across disease groups and demographics. Hence, these data could be formulated as multivariate complex object data, such as probability densities, histograms, and observations on a tree. Traditional statistical methods would often fail to apply, as they are sampled from an arbitrary non-Euclidean metric space. In this paper we propose novel, nonparametric, graph-based two-sample tests for object data with the same structure of repeated measures. We treat the repeatedly measured object data as multivariate object data, which requires the same number of repeated observations per individual but eliminates any assumptions on the errors of the repeated observations. A set of test statistics are proposed to capture various possible alternatives. We derive their asymptotic null distributions under the permutation null. These tests exhibit substantial power improvements over the existing methods while controlling the type I errors under finite samples as shown through simulation studies. The proposed tests are demonstrated to provide additional insights on the location, inter- and intra-individual variability of the daily physical activity distributions in a sample of studies for mood disorders.

E-Prevention: Advanced Support System for Monitoring and Relapse Prevention in Patients with Psychotic Disorders Analyzing Long-Term Multimodal Data from Wearables and Video Captures

Wearable technologies and digital phenotyping foster unique opportunities for designing novel intelligent electronic services that can address various well-being issues in patients with mental disorders (i.e., schizophrenia and bipolar disorder), thus having the potential to revolutionize psychiatry and its clinical practice. In this paper, we present e-Prevention, an innovative integrated system for medical support that facilitates effective monitoring and relapse prevention in patients with mental disorders. The technologies offered through e-Prevention include: (i) long-term continuous recording of biometric and behavioral indices through a smartwatch; (ii) video recordings of patients while being interviewed by a clinician, using a tablet; (iii) automatic and systematic storage of these data in a dedicated Cloud server and; (iv) the ability of relapse detection and prediction. This paper focuses on the description of the e-Prevention system and the methodologies developed for the identification of feature representations that correlate with and can predict psychopathology and relapses in patients with mental disorders. Specifically, we tackle the problem of relapse detection and prediction using Machine and Deep Learning techniques on all collected data. The results are promising, indicating that such predictions could be made and leading eventually to the prediction of psychopathology and the prevention of relapses.

Objective assessment of motor activity in a clinical sample of adults with attention-deficit/hyperactivity disorder and/or cyclothymic temperament

BACKGROUND

Most research on patterns of motor activity has been conducted on adults with mood disorders, but few studies have investigated comorbid attention-deficit/hyperactivity disorder (ADHD) or temperamental factors that may influence the clinical course and symptoms. Cyclothymic temperament (CT) is particularly associated with functional impairment. Clinical features define both disorders, but objective, biological markers for these disorders could give important insights with regard to pathophysiology and classification.

METHODS

Seventy-six patients, requiring diagnostic evaluation of ADHD, mood or anxiety disorders were recruited. A comprehensive diagnostic evaluation, including the CT scale of the Temperament Evaluation of Memphis, Pisa, Paris and San Diego - Auto-questionnaire (TEMPS-A), neuropsychological tests and actigraphy, was performed. ADHD was diagnosed according to the DSM-IV criteria. There was a range of different conditions in this clinical sample, but here we report on the presence of CT and ADHD in relation to motor activity. Twenty-nine healthy controls were recruited. We analyzed motor activity time series using linear and nonlinear mathematical methods, with a special focus on active and inactive periods in the actigraphic recordings.

RESULTS

Forty patients fulfilled the criteria for ADHD, with the remainder receiving other psychiatric diagnoses (clinical controls). Forty-two patients fulfilled the criteria for CT. Twenty-two patients fulfilled the criteria for ADHD and CT, 18 patients met the criteria for ADHD without CT, and 15 patients had neither. The ratio duration of active/inactive periods was significantly lower in patients with CT than in patients without CT, in both the total sample, and in the ADHD subsample.

CONCLUSIONS

CT is associated with objectively assessed changes in motor activity, implying that the systems regulating motor behavior in these patients are different from both healthy controls and clinical controls without CT. Findings suggest that actigraphy may supplement clinical assessments of CT and ADHD, and may provide an objective marker for CT.

Free-Living Standing Activity as Assessed by Seismic Accelerometers and Cognitive Function in Community-Dwelling Older Adults: The MIND Trial

BACKGROUND

Few older adults are able to achieve recommended levels of moderate-vigorous physical activity despite known cognitive benefits. Alternatively, less intense activities such as standing can be easily integrated into daily life. No existing study has examined the impact of free-living standing activity during daily life as measured by a device on cognition in older adults. Our purpose was to examine the association between free-living standing activity and cognitive function in cognitively healthy older adults.

METHOD

Participants were 98 adults aged 65 years or older from the ongoing MIND trial (NCT02817074) without diagnoses or symptoms of mild cognitive impairment or dementia. Linear regression analyses tested cross-sectional associations between standing activity (duration and intensity from the MoveMonitor+ accelerometer/gyroscope) and cognition (4 cognitive domains constructed from 12 cognitive performance tests).

RESULTS

Participants were on average 69.7 years old (SD = 3.7), 69.4% women, and 73.5% had a college degree or higher. Higher mean intensity of standing activity was significantly associated with higher levels of perceptual speed when adjusting for age, gender, and education level. Each log unit increase in standing activity intensity was associated with 0.72 units higher of perceptual speed (p = .023). When we additionally adjusted for cognitive activities and moderate-vigorous physical activity, and then also for body mass index, depressive symptoms, prescription medication use, and device wear time, the positive association remained.

CONCLUSIONS

These findings should be further explored in longitudinal analyses and interventions for cognition that incorporate small changes to free-living activity in addition to promoting moderate-vigorous physical activity.

Post-contact immobility and half-lives that save lives

A wide variety of animals become completely immobile after initial contact with a potential predator. This behaviour is considered to be a last-ditch escape strategy. Here, we test the hypothesis that such immobility should have an extremely unpredictable duration. We find that it spans more than three orders of magnitude in antlion larvae. We also analyse the second period of immobility that follows the first bout of immobility, and consider the distributions of both first and second immobility periods within the context of the intermittence that characterizes the movement of most organisms. Both immobility durations were fitted best by exponential distributions. Therefore, both were characterized by high variability and hence, unpredictability. The immobility half-life, its mean duration and standard deviation were greater for the first than the second immobility. Furthermore, individual consistency was weak or absent in repeated measures of the first immobility and between the first and second immobilities. Our quantitative approach can be replicated across taxa and would help link an understanding of immobility after an initial predator contact in both vertebrates and invertebrates. To facilitate this, we contend that the terminology should be simplified, and we advocate the use of the term post-contact immobility (PCI).

eHealth tools for assessing psychomotor activity in schizophrenia: a systematic review

Objective:

Psychomotor abnormalities are relevant symptoms in the clinical presentation of schizophrenia, and assessing them could facilitate monitoring. New technologies can measure psychomotor activity objectively and continuously, but evidence on the topic is scarce. Our aim is to systematically review the existing evidence about eHealth tools for assessing psychomotor activity in patients diagnosed with schizophrenia.

Method:

We performed a systematic search of the PubMed and Embase databases and identified 15 relevant articles on eHealth tools for assessing psychomotor activity in schizophrenia.

Results:

eHealth devices accurately assessed psychomotor activity and were well accepted. Abnormalities in psychomotor activity helped differentiate between different subtypes of schizophrenia. Abnormal increases in psychomotor activity were correlated with acute presentations, while lower activity was associated with relapses, deterioration, and negative symptoms.

Conclusion:

Actigraphy is still the preferred eHealth device in research settings, but mobile applications have great potential. Further studies are needed to explore the possibilities of psychomotor monitoring and mobile health applications for preventing relapses in schizophrenia. eHealth could be useful for monitoring psychomotor activity, which might help prevent relapses.

Calibration and validation of accelerometry to measure physical activity in adult clinical groups: A systematic review

A growing body of research calibrating and validating accelerometers to classify physical activity intensities has led to a range of cut-points. However, the applicability of current calibration protocols to clinical populations remains to be addressed. The aim of this review was to evaluate the accuracy of the methods for calibrating and validating of accelerometers to estimate physical activity intensity thresholds for clinical populations. Six databases were searched between March and July to 2017 using text words and subject headings. Studies developing moderate-to-vigorous intensity physical activity cut-points for adult clinical populations were included. The risk of bias was assessed using the health measurement instruments and a specific checklist for calibration studies. A total of 543,741 titles were found and 323 articles were selected for full-text assessment, with 11 meeting the inclusion criteria. Twenty-three different methods for calibration were identified using different models of ActiGraph and Actical accelerometers. Disease-specific cut-points ranged from 591 to 2717 counts·min-1 and were identified for two main groups of clinical conditions: neuromusculoskeletal disorders and metabolic diseases. The heterogeneity in the available clinical protocols hinders the applicability and comparison of the developed cut-points. As such, a mixed protocol containing a controlled laboratory exercise test and activities of daily-life is suggested. It is recommended that this be combined with a statistical approach that allows for adjustments according to disease severity or the use of machine learning models. Finally, this review highlights the generalisation of cut-points developed on healthy populations to clinical populations is inappropriate.

Assessment of Fractal Characteristics of Locomotor Activity of Geriatric In-Patients With Alzheimer's Dementia

INTRODUCTION

Many physiological signals yield fractal characteristics, i.e., finer details at higher magnifications resemble details of the whole. Evidence has been accumulating that such fractal scaling is basically a consequence of interaction-dominant feedback mechanisms that cooperatively generate those signals. Neurodegenerative diseases provide a natural framework to evaluate this paradigm when this cooperative function declines. However, methodological issues need to be cautiously taken into account in order to be able to provide reliable as well as valid interpretations of such signal analyses.

METHODS

Two conceptually different fractal analyses, i.e., detrended fluctuation analysis (DFA) and analysis of cumulative distributions of durations (CDDs), are applied to actigraphy data of 36 geriatric in-patients diagnosed with dementia. The impact of the used time resolution for data acquisition on the assessed fractal outcome parameters is particularly investigated. Moreover, associations between these parameters and scores from the Mini-Mental-State-Examination and circadian activity parameters are explored.

RESULTS

Both analyses yield significant deviations from (mono-)fractal scaling over the entire considered time range. DFA provides robust measures for the observed break-down of fractal scaling. In contrast, analysis of CDDs results in measures which highly fluctuate with respect to the time resolution of the assessed data which affects also further derived quantities such as scaling exponents or associations with other (clinically relevant) assessed parameters.

DISCUSSION

To scrutinize actigraphic signal characteristics and especially their (deviations from) fractal scaling may be a useful tool for aiding diagnosis, characterization, and monitoring of dementia. However, results may, besides contextual aspects, also substantially depend on specific methodological choices. In order to arrive at both reliable and valid interpretations, these complications need to be carefully elaborated in future research.

The Validity and Value of Self-reported Physical Activity and Accelerometry in People With Schizophrenia: A Population-Scale Study of the UK Biobank

BACKGROUND

Previous physical activity (PA) research in schizophrenia has relied largely upon self-report measures. However, the accuracy of this method is questionable. Obtaining accurate measurements, and determining what may influence PA levels in schizophrenia, is essential to understand physical inactivity in this population. This study examined differences in self-reported and objectively measured PA in people with schizophrenia and the general population using a large, population-based dataset from the UK Biobank.

METHODS

Baseline data from the UK Biobank (2007-2010) were analyzed; including 1078 people with schizophrenia (54.19 ± 8.39 years; 55% male) and 450549 without (56.44 ± 8.11; 46% male). We compared self-reported PA with objectively measured accelerometry data in schizophrenia and comparison samples. We also examined correlations between self-report and objective measures.

RESULTS

People with schizophrenia reported the same PA levels as those without, with no differences in low, moderate, or vigorous intensity activity. However, accelerometry data showed a large and statistically significant reduction of PA in schizophrenia; as people with schizophrenia, on average, engaged in less PA than 80% of the general population. Nonetheless, within the schizophrenia sample, total self-reported PA still held significant correlations with objective measures.

CONCLUSIONS

People with schizophrenia are significantly less active than the general population. However, self-report measures in epidemiological studies fail to capture the reduced activity levels in schizophrenia. This also has implications for self-report measures of other lifestyle factors which may contribute toward the poor health outcomes observed in schizophrenia. Nonetheless, self-report measures may still be useful for identifying how active individuals with schizophrenia relative to other patients.

Criticality in the brain: A synthesis of neurobiology, models and cognition

Cognitive function requires the coordination of neural activity across many scales, from neurons and circuits to large-scale networks. As such, it is unlikely that an explanatory framework focused upon any single scale will yield a comprehensive theory of brain activity and cognitive function. Modelling and analysis methods for neuroscience should aim to accommodate multiscale phenomena. Emerging research now suggests that multi-scale processes in the brain arise from so-called critical phenomena that occur very broadly in the natural world. Criticality arises in complex systems perched between order and disorder, and is marked by fluctuations that do not have any privileged spatial or temporal scale. We review the core nature of criticality, the evidence supporting its role in neural systems and its explanatory potential in brain health and disease.