Salīdzināt metodes

	Accelerometer Cut-Point Calibration	Time-Motion Analysis of Match Play
Nozare	Sport Leisure Studies	Sport Leisure Studies
Saime	Regression model	Process / pipeline
Izcelsmes gads	1998	1976
Autors	Patty S. Freedson, Edward Melanson & John Sirard; Kelly R. Evenson et al.	Thomas Reilly & V. Thomas; Jonathan Bloomfield, Remco Polman & Peter O'Donoghue
Tips	Calibration regression / ROC model mapping accelerometer counts to activity intensity	Observational pipeline for quantifying locomotor demands of competition
Pirmavots	Freedson, P. S., Melanson, E., & Sirard, J. (1998). Calibration of the Computer Science and Applications, Inc. accelerometer. Medicine and Science in Sports and Exercise, 30(5), 777-781.	Carling, C., Bloomfield, J., Nelsen, L., & Reilly, T. (2008). The role of motion analysis in elite soccer: contemporary performance measurement techniques and work rate data. Sports Medicine, 38(10), 839-862.
Citi nosaukumi	Activity Count Calibration, Intensity Threshold Derivation, Accelerometer MET Calibration, Cut-Point Derivation	Work-Rate Analysis, Movement Analysis, Locomotor Demand Analysis, Match Activity Profiling
Saistītās	3	3
Kopsavilkums	Accelerometer cut-point calibration solves the central translation problem of objective physical-activity measurement: a wearable accelerometer outputs dimensionless 'counts,' but researchers and health guidelines speak in intensities — sedentary, light, moderate, vigorous. Calibration establishes the count thresholds that map the device's output onto those intensity categories. Patty Freedson, Edward Melanson, and John Sirard's 1998 study of the CSA (later ActiGraph) accelerometer set the template, regressing measured energy expenditure in METs on accelerometer counts during treadmill walking and running and solving the regression for the counts corresponding to moderate (3 METs) and vigorous (6 METs) activity. Later work, exemplified by Evenson and colleagues' 2008 calibration for children, increasingly used receiver-operating-characteristic (ROC) analysis to find the cut-point that best discriminates intensity categories. The result in both cases is a small set of count thresholds that turn raw accelerometer data into minutes of activity at each intensity.	Time-motion analysis quantifies the physical demands of competition by classifying a player's continuous movement into discrete categories — standing, walking, jogging, running, sprinting — and measuring how much time and distance is spent in each. Thomas Reilly and V. Thomas's 1976 study of professional footballers established the template: hand-tracking players through a match, classifying their locomotion into movement bands, and showing that different positional roles impose different work-rates, with midfielders covering the most ground. The method matured through video-based work such as Bloomfield, Polman and O'Donoghue's 2007 analysis of physical demands by position in the Premier League, and has since been transformed by GPS and optical tracking that record position continuously and automatically. Across these technologies the analytical logic is constant: turn continuous locomotion into categorized time-and-distance metrics that characterize the locomotor demands of the sport.