Understanding Sway Jerk
Sway jerk describes how quickly body sway acceleration changes. It is useful when balance data looks similar by distance alone. Two trials can have equal sway size. One trial can still include sharper corrections. Jerk helps reveal that hidden roughness.
The Horak style approach often uses AP and ML movement traces. AP means front to back. ML means side to side. The calculator combines both axes. It first prepares the signal. Then it estimates derivatives at each sample. If you enter position data, it differentiates to acceleration. Then it differentiates again to jerk. If you enter acceleration data, it differentiates once to jerk.
Formula Logic
The main result is resultant jerk integral. It sums squared AP jerk plus squared ML jerk across time. A higher value means the sway path changed acceleration more abruptly. The tool also reports mean jerk power. This divides the integral by trial duration. RMS jerk shows typical jerk magnitude. Peak jerk highlights the largest instant correction.
Data Quality
Good data preparation matters. Use a steady sampling rate. Keep units consistent. Remove obvious recording errors before analysis. Use the smoothing window only when the trace contains high frequency noise. Too much smoothing can hide real corrective movement. The trim fields help exclude setup motion at the start and relaxation motion at the end.
This page is designed for research review, teaching, and screening workflows. It is not a medical diagnosis. Compare trials recorded with the same equipment. Keep stance, footwear, vision, and surface conditions consistent. A firm surface with eyes open should not be mixed with foam or eyes closed trials unless the comparison is intended.
Practical Use
The example table shows common inputs and expected outputs. Your own results can be exported for records. The CSV file is best for spreadsheets. The PDF file is best for sharing a compact report. Always store the raw AP and ML data too. Raw data lets you repeat the calculation later.
Use the notes field to document subject posture, sensor placement, and trial condition. These details make the result easier to interpret. They also support careful repeat testing. Over time, consistent sway jerk values can help describe balance smoothness with more precision and less guesswork.