Integrated sensor insole systems for application in knee osteoarthritis: FeetMe® versus Moticon®

The analysis of the human movement helps us to understand musculoskeletal disorders, such as the mechanical loading of the knee joint, which, if altered, demonstrates the increase of risk for knee osteoarthritis. Because this leads to a great number of disability in the elder population, it is essential for the development of treatments to assess the load. Walking involves a complex interaction of muscle forces on bones, rotations through multiple joints and physical forces acting on the body. Gait can be analyzed with simple observation or three-dimensional analysis including kinematics and kinetics, muscle activity and foot pressure, allowing designs of procedures tailored to the individual needs of patients. Objective Walking biomechanics can be assessed outside of a specialist gait laboratory with the use of wearable sensors. For the implementation in interventional trials with osteoarthritis patients, off-the-shelf inertial measurement units and foot plantar pressure insoles are intended to collect the patient’s lower limb inertial, foot pressure and spatiotemporal gait parameter data during habitual walking. With this data, angles in hip, knee and ankle as well as spatiotemporal parameters, such as stride length and cadence and the vertical component of the ground reaction force shall be assessed. The metrics of knee loading and gait characteristics change in function over time are then used to identify patterns and potential endpoints for future trials. In this work, two fully integrated wireless sensor insole systems by FeetMe® and Moticon® were investigated and compared with respect to technical specifications, usability and validity regarding spatiotemporal parameters and vertical ground reaction force. The reference system for the validation of the two insoles was an instrumented treadmill, allowing for a controlled setup with respect to gait speed and for walking of longer distances during data acquisition. This thesis intends to enable the selection of the appropriate insole system given the needs that are requested for their application in clinical trials with respect to system usability, spatiotemporal gait parameter and ground reaction force measurement. Methods The methods to compare the two insole systems, which would provide information about the differences in usability, spatiotemporal gait parameters (gait cycle time, cadence, stride length, walking speed, double support, stance and swing phase) and vertical ground reaction force calculations between FeetMe® and Moticon® for an appropriate system selection for clinical trials, consisted of three sections. At first the two systems were compared regarding technical specifications. The second part consisted of a usability review with respect to the insole’s application in large clinical trials. The third part contained a comparison of the acquired data including a validation with an instrumented treadmill as ground truth. The data acquisition was performed by one healthy subject (the author of this thesis) wearing the insoles while walking at three different speeds (0.69, 1.00 and 1.31 m/s) with different footwear (a hard dress shoe, a soft running shoe and wearing the insoles without a shoe, fixed to the foot with a sock and rubber bands) and in application of different gait styles (normal, toe-out, toe-in and limping gait) that are common in patients with knee osteoarthritis. Additional data was assessed by walking on a 15 % slope. Results From a technical perspective, the insoles provided the same features with integrated inertial and capacitive pressure sensors, with a higher number of pressure sensors by FeetMe® (18 compared to VII 16 of Moticon®) as well as a higher sampling frequency (up to 140 Hz for FeetMe® vs 100 Hz for Moticon®). The usability review mainly showed challenges in battery charging and data transfer. The charging of the FeetMe® insole blocks it for further measurements since the battery is not interchangeable, while the Moticon® insole has long data transfer times once the insole memory is full, with additional risk of losing data when the wireless connection is lost. The validation showed that both insoles were in high agreement with the reference system in gait cycle time, cadence and step time. Mean absolute differences observed in spatial parameters were for stride length 0.019 m for FeetMe® and 0.12 m for Moticon®, and for walking speed 0.017 m/s for FeetMe® and 0.093 m/s for Moticon®. The timely detection of heel-strike and toe-off events showed to be the most challenging for both insoles showing in double support phase (DSP), swing and stance phase. The mean difference in DSP (upper/lower limit of agreement) for FeetMe® was 0.11 % (5.57/-5.34) and for Moticon® 9.13 % (13.46/4.79). While FeetMe® showed a very close mean DSP to the instrumented treadmill with a deviation of ±5 %, Moticon® had a constant underestimation of the DSP by on average 9.13 %, but showed a slightly smaller deviation in DSP than FeetMe®. The vertical ground reaction force (GRF) showed a general overestimation by both insoles but was dependent on the footwear. The FeetMe® insoles in combination with the soft running shoe showed the best results when compared to the instrumented treadmill as reference, with an overestimation of the mean vertical GRF during stance of 13.5 %. Conclusion Both insoles have shown characteristics that favor either of them in certain scenarios, depending on their use in a clinical setup and what variables they are intended to investigate. This work allows for the selection of the appropriate insole system, if their application is known and carefully planned