Current treatments of rotational deformities of long bones in children are osteotomies and fixations. In recent years, the use of guided growth for correction of rotational deformities has been reported in several pre-clinical and clinical studies. Various techniques have been used, and different adverse effects, like growth retardation and articular deformities, have been reported. We tested a novel plate concept intended for correction of rotational deformities of long bones by guided growth, with sliding screw holes to allow for longitudinal growth, in a porcine model. Twelve, 12-week-old female porcines were included in the study. Surgery was performed on the left femur. The right femur was used as control. Plates were placed distally to induce external rotation, as longitudinal growth occurred. CT-scans of the femurs were processed to 3-D models and used for measuring rotation.Introduction
Method
Adolescent Idiopathic Scoliosis (AIS) is a three-dimensional deformity of the spine with unclear etiology. Due to the asymmetry of lateral curves, there are differences in the muscle activation between the convex and concave sides. This study utilized a comprehensive thoracic spine and ribcage musculoskeletal model to improve the biomechanical understanding of the development of AIS deformity and approach an explanation of the condition. In this study, we implemented a motion capture model using a generic rigid-body thoracic spine and ribcage model, which is kinematically determinate and controlled by spine posture obtained, for instance, from radiographs. This model is publicly accessible via a GitHub repository. We simulated gait and standing models of two AIS (averaging 15 years old, both with left lumbar curve and right thoracic curve averaging 25 degrees) and one control subject. The marker set included extra markers on the sternum and the thoracic and lumbar spine. The study was approved by the regional Research Ethics Committee (Journal number: H17034237).Introduction
Methods
Gait measurements can vary due to various intrinsic and extrinsic factors, and this variability becomes more pronounced using inertial sensors in a free-living environment. Therefore, identifying and quantifying the sources of variability is essential to ensure measurement reliability and maintain data quality. This study aimed to determine the variability of daily accelerations recorded by an inertial sensor in a group of healthy individuals. Ten participants, four males and six females, with a mean age of 50 years (range: 29–61) and BMI of 26.9 kg/m2 (range: 21.4–36.8), were included. A single accelerometer continuously recorded lower limb accelerations over two weeks. We extracted and analyzed the accelerations of three consecutive strides within walking bouts if the time difference between the bouts was more than two hours. Multivariate mixed-effects modeling was performed on both the discretized acceleration waveforms at 101 points (0–100) and the harmonics of the signals in the frequency domain to determine the variance components for different subjects, days, bouts, and steps as the random effect variables. Intraclass correlation coefficients (ICCs) were calculated for between-day, between-bout, and between-step comparisons. The results showed that the ICCs for the between-day, between-bout, and between-step comparisons were 0.73, 0.82, 0.99 for the vertical axis; 0.64, 0.75, 0.99 for the anteroposterior axis; and 0.55, 0.96, 0.97 for the mediolateral axis. For the signal harmonics, the respective ICCs were 0.98, 0.98, 0.99 for the vertical axis; 0.54, 0.93, 0.98 for the anteroposterior axis; and 0.69, 0.78, 0.95 for the mediolateral axis. Overall, this study demonstrated that accelerations recorded continuously for multiple days in a free-living environment exhibit high variability, mainly between days, and some variability arising from differences between walking bouts during different times within days. However, reliable and repeatable gait measurements can be obtained by identifying and quantifying the sources of variability.
The tendency towards using inertial sensors for remote monitoring of the patients at home is increasing. One of the most important characteristics of the sensors is sampling rate. Higher sampling rate results in higher resolution of the sampled signal and lower amount of noise. However, higher sampling frequency comes with a cost. The main aim of our study was to determine the validity of measurements performed by low sampling frequency (12.5 Hz) accelerometers (SENS) in patients with knee osteoarthritis compared to standard sensor-based motion capture system (Xsens). We also determined the test-retest reliability of SENS accelerometers. Participants were patients with unilateral knee osteoarthritis. Gait analysis was performed simultaneously by using Xsens and SENS sensors during two repetitions of over-ground walking at a self-selected speed. Gait data from Xsens were used as an input for AnyBody musculoskeletal modeling software to measure the accelerations at the exact location of two defined virtual sensors in the model (VirtualSENS). After preprocessing, the signals from SENS and VirtualSENS were compared in different coordinate axes in time and frequency domains. ICC for SENS data from first and second trials were calculated to assess the repeatability of the measurements. We included 32 patients (18 females) with median age 70.1[48.1 – 85.4]. Mean height and weight of the patients were 173.2 ± 9.6 cm and 84.2 ± 14.7 kg respectively. The correlation between accelerations in time domain measured by SENS and VirtualSENS in different axes was r = 0.94 in y-axis (anteroposterior), r = 0.91 in x-axis (vertical), r = 0.83 in z-axis (mediolateral), and r = 0.89 for the magnitude vector. In frequency domain, the value and the power of fundamental frequencies (F0) of SENS and VirtualSENS signals demonstrated strong correlation (r = 0.98 and r = 0.99 respectively). The result of test-retest evaluation showed excellent repeatability for acceleration measurement by SENS sensors. ICC was between 0.89 to 0.94 for different coordinate axes. Low sampling frequency accelerometers can provide valid and reliable measurements especially for home monitoring of the patients, in which handling big data and sensors cost and battery lifetime are among important issues.
