Lower limb fractures are commonly treated with cast immobilization, and as a main consequence of strict immobilization this typically leads to loss in muscle mass, decrease of bone density and decline in functional abilities. Body-worn sensors are increasingly used to assess outcome in clinical trials by providing objective mobility parameters in a real-world environment. The aim of this study is to investigate the usability aspects and potential changes in mobility parameters in partial-immobilization patients in real-world conditions. Six healthy young males (age 22.2 ± 1.2 years; weight 76.5 ± 6.7 kg, height 185.8 ± 6.1 cm. Mean ± standard deviation) wore a leg cylinder cast with walker boot to immobilize their dominant leg for two consecutive weeks. Subjects were asked to continuously wear a tri-axial accelerometer on the waist (actibelt) during waking hours for 6 weeks including 2 weeks before, during and after cast immobilisation. The total amount of days of continuous recording was 339 days with a total wearing time of 120 days. Software packages which allow to detect steps and to estimate real-world walking speed were used to analyse the accelerometry data. It was suspected that knee immobilization would affect strongly the wave form of the signal with an impact on the accuracy of the speed algorithm, whereas the step detection should be more robust. This effect was confirmed in a preliminary study performed to quantify the accuracy under immobilization conditions. On the other hand, step numbers are known to be sensitive to fluctuations in wearing time which was not uniform throughout the entire study. We concluded that in this setting step frequency is the most reliable parameter. Step frequency showed a systematic decrease in the values during the immobilization period which recovered to pre-immobilisation values after cast removal. This confirms the usability of accelerometry and sensitivity of its mobility parameters for clinical outcome assessment.

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.