Capturing objective data of the postoperative changes in the mobility of patients is expected to generate a better understanding of the effect of postoperative treatment. Until recently, the collection of gait-related data was limited to controlled clinical environments. The emergence of accurate wearable accelerometers with sufficient runtime, however, enables the long-term measurement and extraction of mobility parameters, such as “real-world walking speed”. An interim analysis of 1967 hours of actibelt data (3D accelerometer, 100 Hz) from 5 patients (planned total 20) with a femur fracture and 5 patients (planned total 20) with a humerus fracture from a geriatric population at two different sites of the university hospital of the Ludwigs-Maximilian-University in Munich was performed. Mobility data was captured during several days of stationary treatment starting directly after surgery and during a short follow-up visit six weeks after the surgery. Preliminary results show an increase of the mean walking speed between the two visits independent of the type of fracture. Patients with a humerus fracture tended to walk faster than patients with a femur fracture during both visits. The data also reveals an unexpected low level of mobility during the stationary stay. Mobile accelerometry can be used to evaluate different postoperative mobilisation strategies and even provide near-time feedback in geriatric trauma patients.

Introduction

Osteoarthritis (OA) is a slow progressive disease and a huge economic burden. A new target for therapy could be a growth factor treatment to prevent the loss of cartilage following injuries to the joint. BMP-7 is a promising candidate for such a novel therapy based on growth factors. In this study we combined the chondroprotective effects of BMP-7 with a novel thermosensitive hydrogel to prevent cartilage degeneration in a murine OA model.

Mobility plays an important role, in particular for patients with osteoporosis and after trauma surgery, both as an outcome and as treatment. Mobility is closely linked to the patient”s quality of life and exercise is a powerful additional treatment option. In order to be able to generate an evidence base to evaluate various surgical and non-surgical treatment options, objective measurements of patient mobility and exercise over a certain time period are needed. Wearables are a promising candidate, with obvious advantages compared to questionnaires and/or PROs. However, when extracting parameters with wearables, one often faces the problem of algorithms not performing well enough for special cases like slow gait speeds or impaired gait, as they typically appear in this patient group. We plan to further extend the applicability of the actibelt system (3D accelerometer, 100Hz), in particular to improve the measurement precision of real-world walking speed in slow and impaired walking. We are using a special measurement wheel including a rotating 3D accelerometer that allows to capture high quality real-world walking speed and distance measurements, and a mobile high resolution camera system. In a first block 20 patients with osteoporosis were included in the study at the Ludwigs-Maximilians-University”s Department of General, Trauma and Reconstructive Surgery in Munich, Germany and equipped with an actibelt. Patients were asked to walk as “normal” as possible, while wearing their usual apparel, in the building and outside the building. They climbed stairs and had to deal with all unexpected “stop and go” events that appear in real-world walking. Various gait parameters will be extracted from the recorded data and compared to the gold standard. We will then tune the existing algorithms as well as new algorithms (e.g. step detection based on continuous wavelet transformation) to explore potential improvements of both step detection and speed estimation algorithms. Further refinement and validation using real world data is warranted.