Automated event detection algorithm for two squatting protocols.

INTRODUCTION: Squatting biomechanics assessed using motion analysis relies on the identification of specific events: start of descent, transition between descent/ascent and end of ascent. Automated identification reduces the time needed to process trials while allowing consistency across studies. The purpose of this study was to develop criteria for the identification of events and apply them to two squatting protocols in pathological patient and typically developing (TD) groups.

METHODS: Thirty-four subjects with hip dysplasia and 41 TD subjects were enrolled in this study. While instrumented with a full-body Plug-In-Gait marker set, participants performed two squatting protocols: a hold squat, where subjects paused for a count of three at their lowest squat depth, and a traditional squat, where the descent phase was immediately followed by the ascent phase. Reviewers analyzed the kinematic/kinetic waveforms of a subset of trials to develop criteria for events. Sagittal plane knee and vertical center of mass velocities were used to identify events and absolute vs. relative thresholds of the peak knee velocity were compared. These criteria were incorporated into an automatic event detection code.

RESULTS: Using a relative threshold algorithm, events were automatically identified in 244 of 259 total trials (94%). For the trials requiring manual placement of events (n=15 trials), there was perfect inter-rater reliability between research personnel.

CONCLUSIONS: The criteria developed for the automatic detection of squatting events was highly successful for both protocols in each participant group and was also highly reliable for research personnel to follow in the few instances where manual placement was necessary.