SummaryBackground/ObjectiveActivity 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.MethodsUsing 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.ResultsIn 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.ConclusionActivity 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.

Physical activity (PA) may need to produce high impacts to be osteogenic. The aim of this study was to identify threshold(s) for defining high impact PA for future analyses in the VIBE (Vertical Impact and Bone in the Elderly) study, based on home recordings with triaxial accelerometers. Recordings were obtained from 19 Master Athlete Cohort (MAC; mean 67.6 years) and 15 Hertfordshire Cohort Study (HCS; mean 77.7 years) participants. Data cleaning protocols were developed to exclude artifacts. Accelerations expressed in g units were categorized into three bands selected from the distribution of positive Y-axis peak accelerations. Data were available for 6.6 and 4.4 days from MAC and HCS participants respectively, with approximately 14 hr recording daily. Three-fold more 0.5-1.0g impacts were observed in MAC versus HCS, 20-fold more 1.0-1.5g impacts, and 140-fold more impacts ≥ 1.5g. Our analysis protocol successfully distinguishes PA levels in active and sedentary older individuals.

Patients undergoing total knee replacement for end stage knee osteoarthritis (OA) become increasingly younger and more demanding. Consequently, outcome assessment tools need to evolve toward objective performance-based measures. We applied a novel approach toward ambulatory biomechanical assessment of physical function using a single inertial sensor located at the pelvis to derive various motion parameters during activities of daily living. We investigated the potential of a clinically feasible battery of tests to define relevant parameters of physical function. We compared preoperative measures of end stage knee OA patients to healthy subjects. Our results show that measures of time yield the highest discriminative capacity to differentiate between groups. Additionally we found disease-dependent and task-specific alterations of movement for inertial sensor-derived motion parameters with good discriminative capacity. The inertial sensor's output quantities seem to capture another clinically relevant dimension of physical function that is supplementary to time. This study demonstrates the potential of inertial sensor-based motion analysis and provides a standardized test feasible for a routine clinical application in the longitudinal follow-up.

Background: It is important to assess physical activity objectively during daily life circumstances, to understand the association between physical activity and diseases and to determine the effectiveness of interventions. Accelerometer-based physical activity monitoring seems a promising method and could potentially capture all four FITT (i.e. Frequency, Intensity, Time, Type) components of physical activity considered by the World Health Organization (WHO).Aim: To assess the four FITT components of physical activity with an accelerometer during daily life circumstances and compare with self-reported levels of physical activity in patients with knee osteoarthritis (OA) and a healthy control group.Methods: Patients (n=30) with end-stage knee OA and age-matched healthy subjects (n=30) were measured. An ambulant tri-axial accelerometer was placed onto the lateral side of the upper leg. Physical activity was measured during four consecutive days. Using algorithm-based peak detection methods in Matlab, parameters covering the four FITT components were assessed. Self-reported physical activity was assessed using the Short questionnaire to assess health enhancing physical activity (SQUASH).Results: Knee OA patients demonstrated fewer walking bouts (154 ±79 versus 215 ±65 resp.; p=0.002), step counts (4402 ±2960 steps/day versus 6943 ±2581 steps/day; p=0.001) and sit-to-stand (STS) transfers (37 ±14 versus 44 ±12; p=0.031) compared to controls. Knee OA patients demonstrated more time sitting (65 ±15% versus 57 ±10% resp.; p=0.029), less time walking (8 ±4% versus 11 ±4% resp.; p=0.014) and lower walking cadence (87 ±11steps/min versus 99 ± 8steps/min resp.; p<0.001). Accelerometer-based parameters of physical activity were moderately-strong (Pearsons’s r= 0.28-0.49) correlated to self-reported SQUASH scores.Conclusion: A single ambulant accelerometer-based physical activity monitor feasibly captures the four FITT components of physical activity and provides more insight into the actual physical activity behavior and limitations of knee OA patients in their daily life.

BackgroundKnee 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.MethodsClinically 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.ResultsSixty-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.ConclusionsFrom 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 registrationGerman Clinical Trials Registry under ‘DRKS00008735’ at 02.12.2015.