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In the medical field, accelerometers are often used for measuring inclination of body segments and activity of daily living (ADL) because they are small and require little power. A drawback of using accelerometers is the poor quality of inclination estimate for movements with large accelerations. This paper describes the design and performance of a Kalman filter to estimate inclination from the signals of a triaxial accelerometer. This design is based on assumptions concerning the frequency content of the acceleration of the movement that is measured, the knowledge that the magnitude of the gravity is 1 g and taking into account a fluctuating sensor offset. It is shown that for measuring trunk and pelvis inclination during the functional three-dimensional activity of stacking crates, the inclination error that is made is approximately 2° root-mean square. This is nearly twice as accurate as compared to current methods based on low-pass filtering of accelerometer signals.