Analysis of accelerometer-derived interpersonal spatial proximities: A calibration, simulation, and validation study. Issue 3 (3rd July 2018)

• Record Type: Journal Article
• Authors: McCullough, Aston K.; Keller, Bryan S.; Qiu, Shumin; Garber, Carol Ewing
• Is Part Of: Measurement in physical education and exercise science. Volume 22:Issue 3(2018)
• Page Start: 275
• Page End: 286
• Publication Date: 2018-07-03
• Subjects: physical activity -- radio -- family -- spatial analysis; Physical fitness -- Testing -- Periodicals; Physical education and training -- Statistical methods -- Periodicals; Physical education and training -- Research -- Periodicals; 613.7
• DOI: 10.1080/1091367X.2018.1437039
• Languages: English
• ISSNs: 1091-367X

Abstract

ABSTRACT: The purpose of this study was to estimate distances from accelerometer-derived Bluetooth signals as a measure of interpersonal spatial proximity. Accelerometer-derived proximity data were collected indoors and outdoors over a 10m range to calibrate simulation models. Proximity data were simulated over 20m (indoor) and 50m (outdoor) ranges. Competing statistical and machine learning models were used to predict simulated distances; the Root-Mean-Square-Error (RMSE) was calculated. Simulation estimates were validated under conditions wherein a single beacon-receiver (SBR) and multiple beacons-receivers (MBR) collected proximity data indoors and outdoors within a ≤10m range. Simulation data showed that a Random Forest (RF) model performed optimally. The validated RF RMSE was ≤2.7 for SBR, and ≥90% of predicted distances were accurately classified as ≤10m. For MBR, ≥67% of predicted distances were accurately classified as ≤10m. Simulation and validation data suggest that distances can be estimated from accelerometer-derived proximity data within a 20m range using a SBR.