Angular momentum, kinetics, and energetics, including total mechanical energy and its rate of change in relation to power exchange, are important quantities when analyzing human motion in sports, physical labor, and rehabilitation. Inertial measurement units (IMU)-based motion capture (MOCAP) systems provide a portable solution for the ambulatory analysis of these quantities which optical MOCAP systems do not offer. Yet, evaluating IMU-based estimates of these quantities by referencing optical systems is limited by the fact that these systems only measure positions, not kinetic and energetic quantities. To evaluate the accuracy of an IMU-based method for estimating kinetic and energetic quantities without using any external reference, firstly, we propose an estimation method only using angular velocity and acceleration signals supplied by an IMU, and apply this to a single rigid body with known mass and inertia. Then, we propose a novel experimental validation method against physical conservation and action/reaction laws that apply during ballistic movements, using a suitably designed and reconfigurable rigid body with a structure of three orthogonal dumb-bells. The results demonstrated that we could estimate the angular momentum, kinetics, and energetics of a rigid body by only using angular velocity and acceleration signals of an IMU, and the estimation accuracy was well evaluated by the proposed validation method. However, the results showed that the errors in original IMU measurements under dynamic conditions especially concerning angular velocity, uncertainties in calculating rigid body parameters, and vibration propagation due to limited rigidity of tubes of the rigid body influenced the estimation accuracy.

Background: The foot progression angle is an important measure used to help patients reduce their knee adduction moment. Current measurement systems are either lab-bounded or do not function in all environments (e.g., magnetically distorted). This work proposes a novel approach to estimate foot progression angle using a single foot-worn inertial sensor (accelerometer and gyroscope). Methods: The approach uses a dynamic step frame that is recalculated for the stance phase of each step to calculate the foot trajectory relative to that frame, to minimize effects of drift and to eliminate the need for a magnetometer. The foot progression angle (FPA) is then calculated as the angle between walking direction and the dynamic step frame. This approach was validated by gait measurements with five subjects walking with three gait types (normal, toe-in and toe-out). Results: The FPA was estimated with a maximum mean error of ~ 2.6° over all gait conditions. Additionally, the proposed inertial approach can significantly differentiate between the three different gait types. Conclusion: The proposed approach can effectively estimate differences in FPA without requiring a heading reference (magnetometer). This work enables feedback applications on FPA for patients with gait disorders that function in any environment, i.e. outside of a gait lab or in magnetically distorted environments.

Background: Parkinson's disease (PD) and essential tremor (ET) are neurodegenerative diseases characterized by movement deficits. Especially in PD, maintaining cyclic movement can be significantly disturbed due to pathological changes in the basal ganglia and the cerebellum. Providing external cues improves timing of these movements in PD and also affects ET. The aim of this study is to determine differences in cortical activation patterns in PD and ET patients during externally and internally cued movements. Methods: Eleven PD patients, twelve ET patients, OFF tremor suppressing medication, and nineteen age-matched healthy controls (HC) were included and asked to perform a bimanual tapping task at two predefined cue frequencies. The auditory cue, a metronome sound presented at 2 or 4 Hz, was alternately switched on and off every 30 s. Tapping at two different frequencies were used since it is expected that different brain networks are involved at different frequencies as has been shown in previous studies. Cortical activity was recorded using a 64-channel EEG cap. To establish the cortical activation pattern in each group, the task related power (TRP) was calculated for each subject. For inter-groups analysis, EEG electrodes for divided into 5 different areas. Results: Inter-group analysis revealed significant differences in areas responsible for motor planning, organization and regulation and involved in initiation, maintenance, coordination and planning of complex sequences of movements. Within the area of the primary motor cortex the ET group showed a significantly lower TRP than the HC group. In the area responsible for combining somatosensory, auditory and visual information both patient groups had a higher TRP than the HC group. Conclusions: Different neurological networks are involved during cued and non-cued movements in ET, PD and HC. Distinct cortical activation patterns were revealed using task related power calculations. Different activation patterns were revealed during the 2 and 4 Hz tapping task indicating different strategies to execute movements at these rates. The results suggest that a including a cued/non-cued tapping task during clinical decision making could be a valuable tool in an objective diagnostic protocol.

There is no objective gold standard to detect tremors. This concerns not only the choice of the algorithm and sensors, but methods are often designed to detect tremors in one specific group of patients during the performance of a specific task. Therefore, the aim of this study is twofold. First, an objective quantitative method to detect tremor windows (TWs) in accelerometer and electromyography recordings is introduced. Second, the tremor stability index (TSI) is determined to indicate the advantage of detecting TWs prior to analysis. Ten Parkinson's disease (PD) patients, ten essential tremor (ET) patients, and ten healthy controls (HC) performed a resting, postural and movement task. Data was split into 3-s windows, and the power spectral density was calculated for each window. The relative power around the peak frequency with respect to the power in the tremor band was used to classify the windows as either tremor or non-tremor. The method yielded a specificity of 96.45%, sensitivity of 84.84%, and accuracy of 90.80% of tremor detection. During tremors, significant differences were found between groups in all three parameters. The results suggest that the introduced method could be used to determine under which conditions and to which extent undiagnosed patients exhibit tremors.

Background: The basal ganglia and cerebellum are brain structures involved in movement initiation, execution and termination. They are thought to be involved in the tremor generation and movement deficits in Parkinson's disease (PD) and essential tremor (ET). Especially in PD, maintaining cyclic movement, such as walking or tapping can be significantly disturbed. Providing external cues improves timing of these movements in PD but its effect on ET has not yet been studied in depth. The aim of this study is to evaluate the usefulness of a bimanual tapping task as a tool during clinical decision making. Method: Hand movements and tremor was recorded using accelerometers and EMG (m. extensor carpi ulnaris) from PD and ET patients and healthy controls during a bimanual tapping task as a way to distinguish PD from ET. All subjects performed the tapping task at two different frequencies, 2 Hz and 4 Hz, with and without the presence of auditory cues. Results: No significant intra-group differences were found in the patient groups. Acceleration data revealed significantly less accurate tapping and more variable tapping in PD than in ET and healthy controls. ET subjects tapped less accurate and with a greater variability than healthy controls during the 4 Hz tapping task. Most interestingly the tapping accuracy improved in PD patients when kinetic tremor was recorded with EMG during the task. Conclusion: Providing ET and PD patients with an external cue results in different tapping performances between patient groups and healthy controls. Furthermore, the findings suggest that kinetic tremor in PD enables patients to perform the task with a greater accuracy. So far this has not been shown in other studies.

Background: Gait retraining interventions using real-time biofeedback have been proposed to alter the loading across the knee joint in patients with knee osteoarthritis. Despite the demonstrated benefits of these conservative treatments, their clinical adoption is currently obstructed by the high complexity, spatial demands, and cost of optical motion capture systems. In this study we propose and evaluate a wearable visual feedback system for gait retraining of the foot progression angle (FPA). Methods: The primary components of the system are inertial measurement units, which track the human movement without spatial limitations, and an augmented reality headset used to project the visual feedback in the visual field. The adapted gait protocol contained five different target angles ranging from 15 degrees toe-out to 5 degrees toe-in. Eleven healthy participants walked on an instrumented treadmill, and the protocol was performed using both an established laboratory visual feedback driven by optical motion capture, and the proposed wearable system. Results and conclusions: The wearable system tracked FPA with an accuracy of 2.4 degrees RMS and ICC=0.94 across all target angles and subjects, when compared to an optical motion capture reference. In addition, the effectiveness of the biofeedback, reflected by the number of steps with FPA value ±2 degrees from the target, was found to be around 50% in both wearable and laboratory approaches. These findings demonstrate that retraining of the FPA using wearable inertial sensing and visual feedback is feasible with effectiveness matching closely an established laboratory method. The proposed wearable setup may reduce the complexity of gait retraining applications and facilitate their transfer to routine clinical practice.