Body temperature patterns during pregnancy and parturition in moose.

Gestation and lactation have high energetic requirements. Up to three-fourths of the gestation period in moose (Alces alces) overlaps with the food-scarce period in winter. During this period, moose deal with the limited forage resources available through hypometabolism with decreased heart rate and body temperature (Tb). Body temperature is also an indicator of oestrus, pregnancy and parturition, which is well documented in several domestic species. In this study, we sought to determine if moose displayed a similar Tb pattern during pregnancy and parturition to domesticated ruminants, and if we could detect parturition by combining Tb and activity data. We studied the Tb pattern of 30 free-ranging adult female moose (≥1.5 years old), equipped with ruminal temperature loggers and GPS collars. We documented a 0.13-0.19°C higher Tb in pregnant compared to non-pregnant moose, depending on the study area with the Tb difference increasing along a south-north gradient, and a drop in Tb and in activity when parturition was imminent. Detection of parturition was highly successful when combining Tb and activity data with an accuracy of 91.5%. Our findings demonstrate that Tb responses to pregnancy and parturition in a wild capital-breeding ruminant are similar to those of domesticated ruminants.

The use of machine learning to detect foraging behaviour in whale sharks: a new tool in conservation.

In this study we present the first attempt at modelling the feeding behaviour of whale sharks using a machine learning analytical method. A total of eight sharks were monitored with tri-axial accelerometers and their foraging behaviours were visually observed. Our results highlight that the random forest model is a valid and robust approach to predict the feeding behaviour of the whale shark. In conclusion this novel approach exposes the practicality of this method to serve as a conservation tool and the capability it offers in monitoring potential disturbances of the species.

Correlations of metabolic rate and body acceleration in three species of coastal sharks under contrasting temperature regimes.

The ability to produce estimates of the metabolic rate of free-ranging animals is fundamental to the study of their ecology. However, measuring the energy expenditure of animals in the field has proved difficult, especially for aquatic taxa. Accelerometry presents a means of translating metabolic rates measured in the laboratory to individuals studied in the field, pending appropriate laboratory calibrations. Such calibrations have only been performed on a few fish species to date, and only one where the effects of temperature were accounted for. Here, we present calibrations between activity, measured as overall dynamic body acceleration (ODBA), and metabolic rate, measured through respirometry, for nurse sharks (Ginglymostoma cirratum), lemon sharks (Negaprion brevirostris) and blacktip sharks (Carcharhinus limbatus). Calibrations were made at a range of volitional swimming speeds and experimental temperatures. Linear mixed models were used to determine a predictive equation for metabolic rate based on measured ODBA values, with the optimal model using ODBA in combination with activity state and temperature to predict metabolic rate in lemon and nurse sharks, and ODBA and temperature to predict metabolic rate in blacktip sharks. This study lays the groundwork for calculating the metabolic rate of these species in the wild using acceleration data.

A Unified Data Architecture for Assessing Motor Symptoms in Parkinson's Disease.

INTRODUCTION: The diagnosis and treatment of Parkinson's disease depend on the assessment of motor symptoms. Wearables and machine learning algorithms have emerged to collect large amounts of data and potentially support clinicians in clinical and ambulant settings. STATE OF THE ART: However, a systematical and reusable data architecture for storage, processing, and analysis of inertial sensor data is not available. Consequently, datasets vary significantly between studies and prevent comparability. CONCEPT: To simplify research on the neurodegenerative disorder, we propose an efficient and real-time-optimized architecture compatible with HL7 FHIR backed by a relational database schema. LESSONS LEARNED: We can verify the adequate performance of the system on an experimental benchmark and in a clinical experiment. However, existing standards need to be further optimized to be fully sufficient for data with high temporal resolution.

Squats in Surveys: Investigating the Feasibility of, Compliance With, and Respondents' Performance on Fitness Tasks in Self-Administered Smartphone Surveys Using Acceleration Data.

Digital health data that accompany data from traditional surveys are becoming increasingly important in health-related research. For instance, smartphones have many built-in sensors, such as accelerometers that measure acceleration so that they offer many new research possibilities. Such acceleration data can be used as a more objective supplement to health and physical fitness measures (or survey questions). In this study, we therefore investigate respondents' compliance with and performance on fitness tasks in self-administered smartphone surveys. For this purpose, we use data from a cross-sectional study as well as a lab study in which we asked respondents to do squats (knee bends). We also employed a variety of questions on respondents' health and fitness level and additionally collected high-frequency acceleration data. Our results reveal that observed compliance is higher than hypothetical compliance. Respondents gave mainly health-related reasons for non-compliance. Respondents' health status positively affects compliance propensities. Finally, the results show that acceleration data of smartphones can be used to validate the compliance with and performance on fitness tasks. These findings indicate that asking respondents to conduct fitness tasks in self-administered smartphone surveys is a feasible endeavor for collecting more objective data on physical fitness levels.

Seasonal Sleep Variations and Their Association With Meteorological Factors: A Japanese Population Study Using Large-Scale Body Acceleration Data.

Seasonal changes in meteorological factors [e.g., ambient temperature (Ta), humidity, and sunlight] could significantly influence a person's sleep, possibly resulting in the seasonality of sleep properties (timing and quality). However, population-based studies on sleep seasonality or its association with meteorological factors remain limited, especially those using objective sleep data. Japan has clear seasonality with distinctive changes in meteorological variables among seasons, thereby suitable for examining sleep seasonality and the effects of meteorological factors. This study aimed to investigate seasonal variations in sleep properties in a Japanese population (68,604 individuals) and further identify meteorological factors contributing to sleep seasonality. Here we used large-scale objective sleep data estimated from body accelerations by machine learning. Sleep parameters such as total sleep time, sleep latency, sleep efficiency, and wake time after sleep onset demonstrated significant seasonal variations, showing that sleep quality in summer was worse than that in other seasons. While bedtime did not show clear seasonality, get-up time varied seasonally, with a nadir during summer, and positively correlated with the sunrise time. Estimated by the abovementioned sleep parameters, Ta had a practically meaningful association with sleep quality, indicating that sleep quality worsened with the increase of Ta. This association would partly explain seasonal variations in sleep quality among seasons. In conclusion, Ta had a principal role for seasonality in sleep quality, and the sunrise time chiefly determined the get-up time.

Research on a physical activity tracking system based upon three-axis accelerometer for patients with leg ulcers.

Venous leg ulcerations are a common problem, with high prevalence in the middle-aged and elderly population, and more attention on research of their physical activities has been paid, as they have great effects on the blood circulation of the lower limb. With enough, appropriate training, the chronic venous ulcerations in the lower limb can be avoided and alleviated, and venous hypertension can be reduced effectively. The study deals with a physical activity tracking system for the patients based on a three-axis accelerometer. The system uses a three-axis accelerometer, a microcontroller, and a wireless Bluetooth module to form a data acquisition platform to acquire accelerations of the lower limb movement, and sends it to a smart mobile phone via the wireless Bluetooth module. The system takes advantages of the smart mobile phone to guide the chronic venous leg ulcers to do prescribed rehabilitation exercises for the lower limb muscles, perform acceleration data preprocessing, wavelet transform and reconstruction, denoising and feature extraction, obtain the results of the rehabilitation exercises, and then give reasonable evaluation and judgment. It is helpful to treat underlying venous reflux, create such an environment that allows skin to grow across an ulcer, and accelerate ulcer healing process consequently.

Sperm allocation in relation to female size in a semelparous salmonid.

To maximize reproductive success, males have to adaptively tailor their sperm expenditure in relation to the quality of potential mates because they require time to replenish their sperm supply for subsequent mating opportunities. Therefore, in mating contexts where males must choose among females in a short period of time, as is the case with semelparous species (which die after one intensely competitive short duration breeding season), selection on sperm allocation can be expected to be a powerful selective agent that shapes the male reproductive success. We quantitatively investigated sperm allocation patterns in chum salmon in relation to perceived female quality by developing a novel method for determining the amount of sperm allocated per ejaculate during spawning bouts. We examined the relationship between sperm expenditure and the body size of paired females (a proxy of egg number and egg quality) in the absence of male-male competition in an experimental channel. The estimated amount of sperm released per spawning event was positively correlated with the size of paired females. However, the number of spawning events a female participated in, which reduces the number of eggs she spawns in each subsequent bout, did not affect this relationship. These results provide support for predictions arising from the sperm allocation hypothesis, male salmon do economize their sperm expenditure in accordance with paired female body size as predicted for their first spawning event, but males overestimate or are unable to assess the quality of females beyond size and provide more sperm than they should in theory when paired with a female that spawned previously. Overall, the observed sperm allocation pattern in chum salmon appears to be adapted to maximize reproductive success assuming female size is an honest indicator of quality, although temporal changes in a female's quality during a reproductive season should be considered when examining sperm allocation strategies.

Mean amplitude deviation calculated from raw acceleration data: a novel method for classifying the intensity of adolescents' physical activity irrespective of accelerometer brand.

BACKGROUND: Using raw acceleration data to assess the intensity of physical activity enables direct comparisons between studies using different accelerometer brands. Mean amplitude deviation (MAD in mg) calculated from resultant tri-axial raw acceleration signal was recently shown to perform best in classifying the intensity of physical activity in adults irrespective of the accelerometer brand. This study compared MAD values and cut-points between two different accelerometers in adolescents. METHODS: Twenty voluntary participants (10 girls and 10 boys) of average age of 14 wore two accelerometers (Actigraph GTX3, Pensacola FL, USA and Hookie AM13, Espoo, Finland) and heart rate monitors (M61, Polar Electro Oy, Kempele, Finland) while completing ten 2-min patterns of typical activities ranging from sedentary behaviour to light, moderate and vigorous-intensity locomotion. Bland-Altman method examined the agreement of MAD values between the accelerometers. Correlation coefficient between individual heart rates and MAD values indicated the validity of pattern-based intensity classification. Generalized ordinal logistic regression determined the intensity-specific MAD cut-points for both accelerometers. RESULTS: MAD values varied from 3 mg (lying supine) to 1609 mg (running). Hookie gave higher values than Actigraph in accelerations exceeding 700 mg. The correlation coefficient between MAD values and heart rates was 0.96 for Hookie and 0.97 for Actigraph. Respectively, the MAD cut-points were 29 and 27 (light), 338 and 330 (moderate), and 604 and 558 (vigorous). CONCLUSIONS: MAD values and cut-points of Hookie and Actigraph showed excellent agreement. Analysing raw accelerometer data with MAD values may enable the comparison of accelerometer results between different studies also in adolescents.