Advances in the science of objective physical activity monitoring : 3rd International Conference on Ambulatory Monitoring of Physical Activity and Movement

Editorial: This theme issue of BJSM presents key papers from the 3rd International Conference on Ambulatory Monitoring of Physical Activity and Movement (ICAMPAM). The July 2013 conference was hosted by the University of Massachusetts and was attended by researchers, clinicians, students and technology vendors for North America, Europe, Australasia and Asia...

An orientation free adaptive step detection algorithm using a smart phone in physical activity monitoring

In this paper we present an Orientation Free Adaptive Step Detection (OFASD) algorithm for deployment in a smart phone for the purposes of physical activity monitoring. The OFASD algorithm detects individual steps and measures a user’s step counts using the smart phone’s in-built accelerometer. The algorithm considers both the variance of an individual’s walking pattern and the orientation of the smart phone. Experimental validation of the algorithm involved the collection of data from 10 participants using five phones (worn at five different body positions) whilst walking on a treadmill at a controlled speed for periods of 5 min. Results indicated that, for steps detected by the OFASD algorithm, there were no significant differences between where the phones were placed on the body (p > 0.05). The mean step detection accuracies ranged from 93.4 % to 96.4 %. Compared to measurements acquired using existing dedicated commercial devices, the results demonstrated that using a smart phone for monitoring physical activity is promising, as it adds value to an accepted everyday accessory, whilst imposing minimum interaction from the user. The algorithm can be used as the underlying component within an application deployed within a smart phone designed to promote self-management of chronic disease where activity measurement is a significant factor, as it provides a practical solution, with minimal requirements for user intervention and less constraints than current solutions.

A probabilistic approach to the anxious home for activity monitoring

This paper describes an approach to representing normal activities in a smart house based on the concept of anxiety. Anxiety is computed as a function of time and is kept low by interactions of an occupant with the various devices in a house. Abnormality is indicated by a lack of activity or the wrong activity which will cause anxiety to rise ultimately raising an alarm, querying the occupant and/or alerting a carer in real-time. Anxiety is formulated using probabilistic models that describe how people interact with devices in combinations. These models can be learnt interactively as the smart house acts pessimistically enquiring of the occupant if what they are doing is normal. Results are presented for a number of kitchen scenarios and for different formulations of anxiety.

The study to track human arm kinematics applying solutions of Wahba’s Problem upon inertial/magnetic sensors

Long-term, off-site human monitoring systems are emerging with respect to the skyrocketing expenditures engaged with rehabilitation therapies for neurological diseases. Inertial/magnetic sensor modules are well known as a worthy solution for this problem. Much attention and effort are being paid for minimizing drift problem of angular rates, yet the rest of kinematic measurements (earth’s magnetic field and gravitational orientation) are only themselves capable enough to track movements applying the theory for solving historicalWahbas Problem. Further, these solutions give a closed form solution which makes it mostly suitable for real time Mo-Cap systems. This paper examines the feasibility of some typical solutions of Wahba’s Problem named TRIAD method, Davenport’s q method, Singular Value Decomposition method and QUEST algorithm upon current inertial/magnetic sensor measurements for tracking human arm movements. Further, the theoretical assertions are compared through controlled experiments with both simulated and actual accelerometer and magnetometer measurements.

Activity and flight trajectory monitoring of mosquito colonies for butomated behaviour analysis

Monitoring and tracking of mosquitoes using image processing is important to facilitate the mosquitos’ behaviour analysis automatically over longer period of times. In this paper, we propose a simple methodology to monitor mosquitos’ activity using multiple cameras optimally placed. In order to ensure optimal camera coverage for the area of observation and desired image quality; we propose to simulate the experimental setup in a 3D virtual environment to obtain one-off optimum camera placement parameters. Our proposed methodology is demonstrated to have improved the activity monitoring process using two cameras for accurate count of occluded mosquitoes and 3D trajectory path reconstruction. This framework will enable working out more challenging tasks of constructing 3D trajectories using information received from multiple low quality cameras, which provide inconsistent and discontinuous trajectories.

Actigraphic monitoring of physical activity in clinical trials in schizophrenia

Schizophrenia is still associated with poor outcome, which is mainly related to negative symptoms, reduced physical activity and low quality of life. Physical activity can be objectively measured without distress using wrist actigraphy. The activity levels during the wake periods of the day have been informative on psychopathology and antipsychotic medication. Several studies demonstrated prominent negative symptoms to be associated with reduced activity levels with strongest correlations in chronic patients. Particularly, the avolition score is correlated with reduced activity levels. Moreover, activity levels differ between DSM-IV schizophrenia spectrum disorders and subtypes as well as between patients treated with olanzapine or risperidone. The longitudinal course of activity levels during an psychotic episode demonstrates considerable variance between subjects. During a psychotic episode patients with low activity levels at baseline experience an amelioration of negative symptoms. In contrast, patients with high activity levels at baseline have stable low negative syndrome scores. Between psychotic episodes less variance is observed. Actigraphy is easily applied in schizophrenia and allows collecting large amounts of crosssectional or longitudinal data. With larger numbers of subjects in controlled trials, continuous recording of activity would foster the detection of different outcome trajectories, which may prove as useful groups to target interventions. In clinical trials, activity monitoring may supplement and validate measures of the negative syndrome and its avolition factor or serve as an outcome marker for physical activity, which is important for metabolic issues and quality of life.