In recent years there has been substantial interest in wearable devices that measure heart rate via photoplethysmography (PPG) sensors placed at the wrist. This is challenging as the wrist PPG signal is severely corrupted by artefacts during motion, and although a number of algorithms are now available commercially and academically there is still a need for improved performance, especially when examining physical activities other than running. To date, algorithms for motion artefact removal from the PPG have focused on the use of a co-located accelerometer to record the motion. In this work, we introduce co-located accelerometer, gyroscope and magnetometer sensors to allow three, six and nine degrees of freedom estimates of the motion present. Assessed during a bike riding task the results show that the heart rate estimation is improved by up 0.57 beats per minute by using the additional information from these new sensors.