Clinical validation of a body-fixed 3D accelerometer and algorithm for activity monitoring in orthopaedic patients

Background/Objective Activity is increasingly being recognized as a highly relevant parameter in all areas of healthcare for diagnosis, treatment, or outcome assessment, especially in orthopaedics where the movement apparatus is directly affected. Therefore, the aim of this study was to develop, describe, and clinically validate a generic activity-monitoring algorithm, satisfying a combination of three criteria. The algorithm must be able to identify, count, and time a large set of relevant daily activities. It must be validated for orthopaedic patients as well as healthy individuals, and the validation must be in a setting that mimics free-living conditions. Methods Using various technical solutions, such as a dual-axis approach, dynamic inclinometry (hip flexion), and semiautomatic calibration (gait speed), the algorithms were designed to count and time the following postures, transfers, and activities of daily living: resting/sitting, standing, walking, ascending and descending stairs, sit–stand transitions, and cycling. In addition, the number of steps per walking bout was determined. Validation was performed with healthy individuals and patients who had undergone unilateral total joint arthroplasty, representing a wide spectrum of functional capacity. Video observation was used as the gold standard to count and time activities in a validation protocol approaching free-living conditions. Results In total 992 and 390 events (activities or postures) were recorded in the healthy group and patient group, respectively. The mean error varied between 0% and 2.8% for the healthy group and between 0% and 7.5% for the patient group. The error expressed in percentage of time varied between 2.0% and 3.0% for both groups. Conclusion Activity monitoring of orthopaedic patients by counting and timing a large set of relevant daily life events is feasible in a user- and patient-friendly way and at high clinical validity using a generic three-dimensional accelerometer and algorithms based on empirical and physical methods. The algorithms performed well for healthy individuals as well as patients recovering after total joint replacement in a challenging validation set-up. With such a simple and transparent method real-life activity parameters can be collected in orthopaedic practice for diagnostics, treatments, outcome assessment, or biofeedback

Objective assessment of physical activity and sedentary behaviour in knee osteoarthritis patients – beyond daily steps and total sedentary time

Abstract Background Knee osteoarthritis patients may become physically inactive due to pain and functional limitations. Whether physical activity exerts a protective or harmful effect depends on the frequency, intensity, time and type (F.I.T.T.). The F.I.T.T. dimensions should therefore be assessed during daily life, which so far has hardly been feasible. Furthermore, physical activity should be assessed within subgroups of patients, as they might experience different activity limitations. Therefore, this study aimed to objectively describe physical activity, by assessing the F.I.T.T. dimensions, and sedentary behaviour of knee osteoarthritis patients during daily life. An additional goal was to determine whether activity events, based on different types and durations of physical activity, were able to discriminate between subgroups of KOA patients based on risk factors. Methods Clinically diagnosed knee osteoarthritis patients (according to American College of Rheumatology criteria) were monitored for 1 week with a tri-axial accelerometer. Furthermore, they performed three functional tests and completed the Knee Osteoarthritis Outcome Score. Physical activity levels were described for knee osteoarthritis patients and compared between subgroups. Results Sixty-one patients performed 7303 mean level steps, 319 ascending and 312 descending steps and 601 bicycle crank revolutions per day. Most waking hours were spent sedentary (61%), with 4.6 bouts of long duration (> 30 min). Specific events, particularly ascending and descending stairs/slopes, brief walking and sedentary bouts and prolonged walking bouts, varied between subgroups. Conclusions From this sample of KOA patients, the most common form of activity was level walking, although cycling and stair climbing activities occurred frequently, highlighting the relevance of distinguishing between these types of PA. The total active time encompassed a small portion of their waking hours, as they spent most of their time sedentary, which was exacerbated by frequently occurring prolonged bouts. In this study, event-based parameters, such as stair climbing or short bouts of walking or sedentary time, were found more capable of discriminating between subgroups of KOA patients compared to overall levels of PA and sedentary time. Thereby, subtle limitations in physical behaviour of KOA-subgroups were revealed, which might ultimately be targeted in rehabilitation programs. Trial registration German Clinical Trials Registry under ‘DRKS00008735’ at 02.12.2015

Are patients with knee osteoarthritis and patients with knee joint replacement as physically active as healthy persons?

Background: It is well documented that patients with knee osteoarthritis (KOA) suffer from reduced physical function and that function of the affected knee is improved after knee joint replacement (KJR). However, it remains uncertain whether patients with KOA are less physically active than healthy people and whether patients increase their level of physical activity after surgery to a level comparable with that of healthy people. The aim of this study was to examine whether patients with KOA are less physically active than healthy participants and whether patients who have undergone KJR show an increased activity and achieve the same level of physical activity as healthy participants 5 years postoperatively. Methods: Fifty-four patients with KOA (29 women; mean age 62 ± 8.6; mean body mass index (BMI) 27 ± 5), 52 patients who had KJR due to KOA 5 years earlier (26 women; mean age 66 ± 7.2; mean BMI 30 ± 5) and 171 healthy participants (76 women, mean age 64 ± 9.7, mean BMI 26 ± 5) were included in this cross-sectional study. The level of physical activity was measured over a mean period of 5.5 days with a triaxial accelerometer mounted on the thigh. Number of daily steps, number of daily short walking bouts of <10 s duration and number of daily transfers from sitting to standing position were recorded. Data were analysed using two sample t tests and were adjusted for age, gender and BMI. Results: Patients with KOA did not differ significantly from healthy participants regarding daily steps (+321, p = 0.50) or daily transfers from sitting to standing (+1.9, p = 0.52) but performed significantly less daily short walking bouts <10 s (−11.9, p = 0.02). Patients after KJR did not differ significantly from healthy participants regarding daily steps (−281, p = 0.60) of transfers from sitting to standing position (−3.2, p = 0.32) but performed significantly less daily short walking bouts <10 s (−21.7, p = 0.001). Conclusion: Patients with KOA and KJR showed no significant reduction in number of daily step counts and transfers from sitting to standing position when compared with matched healthy controls. However, the number of short walking bouts was reduced in patients with KOA and by twice as much in patients with KJR. This indicates that KOA and treatment with KJR hardly affect health-related general activity but do affect specific physical activity behaviour potentially indicative of KOA or post-KJR functional limitations. The translational potential of this article: Activity monitoring with an accelerometer-based method gives insights into health-related general activity levels such as total daily steps and specific parameters such as short walking bouts, which may serve as an objective outcome measure in clinical practice. Keywords: Accelerometry, Activity monitoring, Knee osteoarthritis, Knee replacement, Physical activit

Clinical validation of a body-fixed 3D accelerometer and algorithm for activity monitoring in orthopaedic patients

\u3cp\u3eBackground/Objective Activity is increasingly being recognized as a highly relevant parameter in all areas of healthcare for diagnosis, treatment, or outcome assessment, especially in orthopaedics where the movement apparatus is directly affected. Therefore, the aim of this study was to develop, describe, and clinically validate a generic activity-monitoring algorithm, satisfying a combination of three criteria. The algorithm must be able to identify, count, and time a large set of relevant daily activities. It must be validated for orthopaedic patients as well as healthy individuals, and the validation must be in a setting that mimics free-living conditions. Methods Using various technical solutions, such as a dual-axis approach, dynamic inclinometry (hip flexion), and semiautomatic calibration (gait speed), the algorithms were designed to count and time the following postures, transfers, and activities of daily living: resting/sitting, standing, walking, ascending and descending stairs, sit–stand transitions, and cycling. In addition, the number of steps per walking bout was determined. Validation was performed with healthy individuals and patients who had undergone unilateral total joint arthroplasty, representing a wide spectrum of functional capacity. Video observation was used as the gold standard to count and time activities in a validation protocol approaching free-living conditions. Results In total 992 and 390 events (activities or postures) were recorded in the healthy group and patient group, respectively. The mean error varied between 0% and 2.8% for the healthy group and between 0% and 7.5% for the patient group. The error expressed in percentage of time varied between 2.0% and 3.0% for both groups. Conclusion Activity monitoring of orthopaedic patients by counting and timing a large set of relevant daily life events is feasible in a user- and patient-friendly way and at high clinical validity using a generic three-dimensional accelerometer and algorithms based on empirical and physical methods. The algorithms performed well for healthy individuals as well as patients recovering after total joint replacement in a challenging validation set-up. With such a simple and transparent method real-life activity parameters can be collected in orthopaedic practice for diagnostics, treatments, outcome assessment, or biofeedback.\u3c/p\u3

Dynamic contrast-enhanced MR imaging of carotid atherosclerotic plaque: model selection, reproducibility, and validation

To compare four known pharmacokinetic models for their ability to describe dynamic contrast material-enhanced magnetic resonance (MR) imaging of carotid atherosclerotic plaques, to determine reproducibility, and to validate the results with histologic findings. The study was approved by the institutional medical ethics committee. Written informed consent was obtained from all patients. Forty-five patients with 30%-99% carotid stenosis underwent dynamic contrast-enhanced MR imaging. Plaque enhancement was measured at 16 time points at approximately 25-second image intervals by using a gadolinium-based contrast material. Pharmacokinetic parameters (volume transfer constant, K(trans); extracellular extravascular volume fraction, v(e); and blood plasma fraction, v(p)) were determined by fitting a two-compartment model to plaque and blood gadolinium concentration curves. The relative fit errors and parameter uncertainties were determined to find the most suitable model. Sixteen patients underwent imaging twice to determine reproducibility. Carotid endarterectomy specimens from 16 patients who were scheduled for surgery were collected for histologic validation. Parameter uncertainties were compared with the Wilcoxon signed rank test. Reproducibility was assessed by using the coefficient of variation. Correlation with histologic findings was evaluated with the Pearson correlation coefficient. The mean relative fit uncertainty (±standard error) for K(trans) was 10% ± 1 with the Patlak model, which was significantly lower than that with the Tofts (20% ± 1), extended Tofts (33% ± 3), and extended graphical (29% ± 3) models (P < .001). The relative uncertainty for v(p) was 20% ± 2 with the Patlak model and was significantly higher with the extended Tofts (46% ± 9) and extended graphical (35% ± 5) models (P < .001). The reproducibility (coefficient of variation) for the Patlak model was 16% for K(trans) and 26% for v(p). Significant positive correlations were found between K(trans) and the endothelial microvessel content determined on histologic slices (Pearson ρ = 0.72, P = .005). The Patlak model is most suited for describing carotid plaque enhancement. Correlation with histologic findings validated K(trans) as an indicator of plaque microvasculature, and the reproducibility of K(trans) was goo