This study is relevant to clinicians and researchers who scan subjects prone to move during image acquisition or use motion sensitive contrasts. Researchers using markers or optical motion tracking could benefit from the novel approach used for orientation estimates.We aim to make in-bore motion tracking more accessible through the use of miniature, low-cost sensors found in a large variety of consumer electronics. Most current external motion tracking techniques rely on a set of translation measurements to estimate orientation^1,2, or a retrograte marker which spatially encodes motion parameters on the marker itself³. This fundamentally limits the minimum size of the apparatus the patient must wear as the reliability of orientation estimates falls off as the marker/s are brought closer together^1,2 or reduced in size³. We identified the need for orientation estimates independent of the imaging pulse sequence that can be estimated at a temporal resolution unattainable by navigator-based methods. Many external motion correction techniques are also limited by complex calibration procedures or an increased level of subject interaction⁴, with line-of-site^1,3 or limited measurement range restricting marker placement^2,3. We address some of these issues using an approach with zero scanner-specific calibration.An MRI compatible sensor array was developed comprising a 3-axis magnetometer, 3-axis accelerometer and 3-axis angular rate gyro (Figure 1). The sensors allow for high temporal resolution (up to 1 kHz data rate) measurements of the scanner’s static magnetic field vector and the earth’s gravitational field vector. Orientation estimates are obtained by comparing vector observations from the accelerometer and magnetometer in the subject frame with measurements of the a priori reference vectors (gravity [-y] and B0 [+z]) in the scanner frame. To reduce the effects of linear accelerations on the gravity vector estimate, a modified version of the non-linear complementary filter proposed by Mahony⁵ et al. (originally designed for unmanned aircraft guidance/control) was introduced, which combines angular rate measurements with the vector-based orientation. All sensor signals were digitised onboard the device where a 32-bit micro-controller implemented the complementary filter with single precision floating point arithmetic. A two step, one-time, calibration of the device was performed to correct misalignment of the 3-axis sensors caused by soldering imperfections and variations in the gains of the sensor axes. Data were transmitted to a laptop over a serial optical link (300 Hz). The laptop acts as a TCIP server on the local measurement network for the scanner to query for the latest orientation estimate. By combining the orientation estimates with translation estimates obtained using three orthogonal high speed linear navigators⁶, full rigid body motion correction is achieved. Translation estimates were obtained in the corrected imaging frame by computing the frequency shift of the raw MR signal relative to a reference acquisition. A multi-channel fitting algorithm improved the stability of the translation estimates (Figure 2). Translation and orientation updates were applied for each line of k-space in a standard 3D spoiled gradient echo pulse sequence (TE 7 ms, TR 12 ms, 256x256x64) with a non-selective RF pulse (Figure 3). Four brain acquisitions were performed in three subjects on a 3 T Siemens Skyra: (1) no motion, correction active, (2) occasional pose changes, correction active, (3) occasional pose changes, no correction, (4) continuous motion, correction active. Motion correction was applied in real-time and corrected images were generated immediately on the scanner. All scans were conducted in accordance with protocols approved by the Faculty of Health Sciences Human Research Ethics Committee of the University of Cape Town.The magnetometer measurements of the fields within the MRI scanner during image acquisition allow for an exceptionally high signal to noise vector reference. This and that gravity and the static magnetic field are almost perfectly orthogonal result in more precise orientation estimates than what are conventionally possible with similar sensor arrangements. Figures 4 and 5 show the motion parameters measured during each of the corrected scans and representative images for all 4 acquisitions in one subject.High temporal resolution orientation estimates enable robust motion correction free from scanner specific calibration despite noise in the translation estimates. Tiny changes in orientation could result in substantial errors on the periphery of the image due to a ‘lever arm’ effect. These artefacts are difficult to correct restrospectively highlighting the importance of reliable orientation tracking. Changes in posture of 0.1 degrees over one TR (12ms) were often observed showing the importance of high temporal resolution correction. State parameters such as angular rate and acceleration could be combined with navigator measurements in future implementations to improve translation estimate accuracy in high frequency applications.