Splining raw kinematic data of standing-bending-lifting movement

• Published in: AIP conference proceedings Vol. 2905; no. 1
• Main Authors: Omar, Nurhidayah, Isa, Munawwarah Solihah Muhammad, Salleh, Ahmad Faizal, Salim, Mohammad Shahril
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Melville American Institute of Physics 05.01.2024
• Subjects: Angular acceleration; Angular velocity; Bending; Biomechanics; Data smoothing; Differentiation; Error analysis; Hoisting; Kinematics; Mathematical analysis; Numerical methods; Smoothing; Spline functions
• ISSN: 0094-243X; 1551-7616
• DOI: 10.1063/5.0172431

Spline functions and digital filtering are two numerical methods normally used by the researchers in the field of biomechanics to perform data smoothing and time differentiation. The objective of this study is to perform data smoothing on the raw kinematic data of a subject performing standing-bending-lifting activity using spline function, and to calculate time differentiation from the kinematic data. Raw data on standing-bending-lifting movement was recorded in Biomechanics Lab, UniMAP. Next, quintic spline function was used to smooth the data and calculate the angular velocity and angular acceleration at L5, L3, L1, MAI and T2. When calculated for one trial, the error estimation between smooth and raw data at L5, L3, L1, MAI, and T2 are 0.008°, 0.003°, 0.003°, 0.004°, and 0.008°, respectively. When calculating for five trials, the average error estimation between smooth and raw data at L5, L3, L1, MAI, and T2 are 0.007°, 0.009°, 0.011°, 0.012°, and 0.012°, respectively. The result shows that the quintic spline is able to produce satisfactory output in data smoothing.