Trial reportPhysiological measurement2011
Calibrating a novel multi-sensor physical activity measurement system.
Trial report in Physiological measurement, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.
- Actigraphy to Measure Physical Activity in the Intensive Care Unit: A Systematic Review.Journal of intensive care medicine · 2020Pooled it
- Choosing the Best Sensor Fusion Method: A Machine-Learning Approach.Sensors (Basel, Switzerland) · 2020Article
- Multi-Sensor Fusion for Activity Recognition-A Survey.Sensors (Basel, Switzerland) · 2019Review
- Virtual Sensors for Optimal Integration of Human Activity Data.Sensors (Basel, Switzerland) · 2019Article
- Virtual Spirometry and Activity Monitoring Using Multichannel Electrical Impedance Plethysmographs in Ambulatory Settings.IEEE transactions on biomedical circuits and systems · 2017Article
- Objective Assessment of Physical Activity: Classifiers for Public Health.Medicine and science in sports and exercise · 2016Article
- Validity and reliability of Nike + Fuelband for estimating physical activity energy expenditure.BMC sports science, medicine & rehabilitation · 2015Article
- Comparison of raw acceleration from the GENEA and ActiGraph™ GT3X+ activity monitors.Sensors (Basel, Switzerland) · 2013Article
- Simple to complex modeling of breathing volume using a motion sensor.The Science of the total environment · 2013Article
- Computational methods for estimating energy expenditure in human physical activities.Medicine and science in sports and exercise · 2012Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
Advancing the field of physical activity (PA) monitoring requires the development of innovative multi-sensor measurement systems that are feasible in the free-living environment. The use of novel analytical techniques to combine and process these multiple sensor signals is equally important. This paper describes a novel multi-sensor 'integrated PA measurement system' (IMS), the lab-based methodology used to calibrate the IMS, techniques used to predict multiple variables from the sensor signals, and proposes design changes to improve the feasibility of deploying the IMS in the free-living environment. The IMS consists of hip and wrist acceleration sensors, two piezoelectric respiration sensors on the torso, and an ultraviolet radiation sensor to obtain contextual information (indoors versus outdoors) of PA. During lab-based calibration of the IMS, data were collected on participants performing a PA routine consisting of seven different ambulatory and free-living activities while wearing a portable metabolic unit (criterion measure) and the IMS. Data analyses on the first 50 adult participants are presented. These analyses were used to determine if the IMS can be used to predict the variables of interest. Finally, physical modifications for the IMS that could enhance the feasibility of free-living use are proposed and refinement of the prediction techniques is discussed.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.