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Orthopaedic Proceedings
Vol. 100-B, Issue SUPP_14 | Pages 72 - 72
1 Nov 2018
Lipperts M Gotink F van der Weegen W Theunissen K Meijer K Grimm B
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3D measurement of joint angles so far has only been possible using marker-based movement analysis, and therefore has not been applied in (larger scale) clinical practice (performance test) and even less so in the free field (activity monitoring). 3D joint angles could provide useful additional information in assessing the risk of anterior cruciate ligament injury using a vertical drop jump or in assessing knee range of motion after total knee arthroplasty. We developed a tool to measure dynamic 3D joint angles using 6 inertial sensors, attached to left and right shank, thigh and pelvis. The same sensors have been used for activity identification in a previous study. To validate the setup in a pilot study, we measured 3D knee and hip angles using the sensors and a Vicon movement lab simultaneously in 3 subjects. Subjects performed drop jumps, squats and ran on the spot. The mean error between Vicon and sensor measurement for the maximum joint angles was 3, 7 and 8 degrees for knee flexion, ad/abduction and rotation respectively, and 9, 7 and 10 degrees for hip flexion, ad/abduction and rotation respectively. No calibration movements were required. A major part of the inaccuracy was caused by soft tissue effects and can partly be resolved by improved sensor attachment. These pilot results show that it is feasible to measure 3D joint angles continuously using unobtrusive light-weight sensors. No movement lab is necessary and therefore the measurements can be done in a free field setting, e.g. at home or during training at a sport club. A more extensive validation study will be performed in the near future.


Orthopaedic Proceedings
Vol. 100-B, Issue SUPP_3 | Pages 85 - 85
1 Apr 2018
Bolink S van Laarhoven S Lipperts M Grimm B
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Introduction

Following primary total knee arthroplasty (TKA), patients experience pain relief and report improved physical function and activity. However, there is paucity of evidence that patients are truly more active in daily life after TKA. The aims of this study were: 1) to prospectively measure physical activity with a wearable motion sensor before and after TKA; 2) to compare patient-reported levels of physical activity with objectively assessed levels of physical activity before and after TKA; 3) to investigate whether differences in physical activity after TKA are related to levels of physical function.

Methods

22 patients (age=66.6 ±9.3yrs; m/f= 12/11; BMI= 30.6 ±6.1) undergoing primary TKA (Vanguard, ZimmerBiomet), were measured preoperatively and 1–3 years postoperatively. Patient-reported outcome measures (PROMs) included KOOS-PS and SQUASH for assessment of perceived physical function and activity resp. Physical activity was assessed during 4 consecutive days in patients” home environments while wearing an accelerometer-based activity monitor (AM) at the thigh. All data were analysed using semi-automated algorithms in Matlab. AM-derived parameters included walking time (s), sitting time (s) standing time (s), sit-to-stand transfers, step count, walking bouts and walking cadence (steps/min). Objective physical function was assessed by motion analysis of gait, sit-to-stand (STS) transfers and block step-up (BS) transfers using a single inertial measurement unit (IMU) worn at the pelvis. IMU-based motion analysis was only performed postoperatively. Statistical comparisons were performed with SPSS and a per-protocol analysis was applied to present the results at follow-up.


Orthopaedic Proceedings
Vol. 100-B, Issue SUPP_4 | Pages 89 - 89
1 Apr 2018
Stoffels A Lipperts M van Hemert W Rijkers K Grimm B
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Introduction

Limited physical activity (PA) is one indication for orthopaedic intervention and restoration of PA a treatment goal. However, the objective assessment of PA is not routinely performed and in particular the effect of spinal pathology on PA is hardly known. It is the purpose of this study using wearable accelerometers to measure if, by how much and in what manner spinal stenosis affects PA compared to age-matched healthy controls.

Patients & Methods

Nine patients (m/f= 5/4, avg. age: 67.4 ±7.7 years, avg. BMI: 29.2 ±3.5) diagnosed with spinal stenosis but without decompressive surgery or other musculoskeletal complaints were measured. These patients were compared to 28 age-matched healthy controls (m/f= 17/11, avg. age: 67.4 ±7.6 years, avg. BMI: 25.3±2.9). PA was measured using a wearable accelerometer (GCDC X8M-3) worn during waking hours on the lateral side of the right leg for 4 consecutive days. Data was analyzed using previously validated activity classification algorithms in MATLAB to identify the type, duration and event counts of postures or PA like standing, sitting, walking or cycling. In addition, VAS pain and OSWESTRY scores were taken. Groups were compared using the t-test or Mann-Whitney U-test where applicable. Correlations between PA and clinical scores were tested using Pearson”s r.


Orthopaedic Proceedings
Vol. 100-B, Issue SUPP_4 | Pages 19 - 19
1 Apr 2018
Martens S Lipperts M Samijo S Walbeehm R Grimm B
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Background

Shoulder pain limits range of motion (ROM) and reduces performing activities of daily living (ADL). Objective assessment of shoulder function could be of interest for diagnosing shoulder pathology or functional assessment of the shoulder after therapy.

The feasibility of 2 wearable inertial sensors for functional assessment to differentiate between healthy subjects and patients with unilateral shoulder pathology is investigated using parameters as asymmetry.

Methods

75 subjects were recruited into this study and were measured for at least 8 h a day with the human activity monitor (HAM) sensor. In addition, patients completed the Disability of the Arm, Should and Hand (DASH) score and the Simple Shoulder Test (SST) score. From 39 patients with a variety of shoulder pathologies 24 (Age: 53.3 ± 10.5;% male: 62.5%) complete datasets were successfully collected. From the 36 age-matched healthy controls 28 (Age: 54.9 ± 5.8;% male = 57.1%) full datasets could be retrieved.

Activity parameters were obtained using a self-developed algorithm (Matlab). Outcome parameters were gyroscope and accelerometry-based relative and absolute asymmetry scores (affected/unaffected; dominant/non-dominant) of movement intensity.


Orthopaedic Proceedings
Vol. 100-B, Issue SUPP_3 | Pages 45 - 45
1 Apr 2018
Sliepen M Mauricio E Lipperts M Grimm B Rosenbaum D
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The significance of physical activity (PA) assessment is widely acknowledged as it can aid in the understanding of pathologies. PA of knee osteoarthritis (KOA) patients has been assessed with varying methods, as it is a disease that is known to impair physical function and activity during daily life. Differences between methods have been described for general outcomes (sport participation or sedentary time), yet failed to describe common activities such as stair locomotion or sit-to-stand (STS) transfers. This study therefore aimed to determine the comparability of various methods to assess daily-life activities in KOA patients.

Sixty-one clinically diagnosed KOA patients wore a tri-axial accelerometer (AX3, Axivity, UK) for one week during waking hours. Furthermore, they performed three physical function tests: a 40-m fast-paced walk test (WT), a timed up-and-go test (TUGT) and a 15 stair-climb test (SCT). Patients were also asked to fill out the Knee Osteoarthritis Outcome Score (KOOS), a KOA-specific questionnaire.

Patients were slightly overweight (average BMI: 27.3±4.8 kg/m2), 60 (±10) years old and predominantly female (53%). The amount of daily level walking bouts was only weakly correlated with the WT performance, representing patients” walking capacity, (ρ=−0.33, p=0.01). Similarly, level-walking bouts during daily life correlated weakly with self-perceived walking capacity addressed by the KOOS (ρ=−0.36, p=0.01). For stair locomotion, a slightly different trend was seen. A moderate correlation was found (ρ=0.65, p<0.001), between the amount of ascending bouts and the objective functional test performance (SCT). However, the subjective assessment of stair ascending limitations (via the KOOS) correlated only weakly with both the functional test performance and the measured level of activity (ρ=−0.30 and −0.35, resp.). Comparable results were found for descending motions. STS transfers during daily life correlated moderately at best with the time to complete the TUGT (ρ=−0.43, p<0.01) and only weakly with the self-perceived effort of STS transfers (ρ=−0.26, p=0.04).

Only weak correlations existed between subjective measures and objective parameters (for both functional tests and daily living activities), indicating that they assess different domains (e.g. self-perceived function vs. actual physical function). Furthermore, when comparing the two objective measures, correlation coefficients increased compared to the subjective methods, yet did not reach strong agreement. These findings suggest that addressing common activities of daily life either subjectively or objectively will result in different patient-related outcomes of a study. Assessment methods should therefore be chosen with caution and compared carefully with other studies.


Orthopaedic Proceedings
Vol. 99-B, Issue SUPP_9 | Pages 62 - 62
1 May 2017
Lipperts M Senden R Heyligers I Grimm B
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Background

The goal of total hip arthroplasty (THA) is to reduce pain, restore function but also activity levels for general health benefits or social participation. Thus evaluating THA patient activity can be important for diagnosis, indication, outcome assessment or biofeedback.

Methods

Physical activity (PA) of n=100 primary THA patients (age at surgery 63 ±8yrs; 49M/51F; 170 ±8cm, 79.8 ±14.0kg) was measured at 8 ±3yrs follow-up. A small 3D accelerometer was worn for 4 successive days during waking hours at the non-affected lateral upper leg. Data was analysed using validated algorithms (Matlab) producing quantitative (e.g. #steps, #transfers, #walking bouts) and qualitative (e.g. cadence, temporal distribution of events) activity parameters. An age matched healthy control group (n=40, 69 ±8yrs, 22M/18F) served as reference.


Orthopaedic Proceedings
Vol. 99-B, Issue SUPP_9 | Pages 63 - 63
1 May 2017
Ahmadinezhad S Lipperts M Senden R Heyligers I Grimm B
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Background

In total knee arthroplasty (TKA), patient reported outcome on pain, function or satisfaction fails to differentiate treatment options. Activity, a consequence of pain-free, well functioning TKA and a satisfied patient, may be a discriminative surrogate metric, especially when objectively measured.

Methods

Habitual activity was measured in TKA patients (n=32, F/M=20/12, age: 72 ±8yrs) at long-term follow-up (9 ±1yrs) and compared to healthy, age matched controls (n=32, F/M=20/12, age: 71 ±9yrs) using a popular questionnaire (SQUASH) and accelerometry. A small 3D accelerometer (X16-mini, GCD Dataconcepts) was worn for 4 successive days during waking hours at the non-affected lateral upper leg. Data was analysed using validated algorithms (Matlab) counting and timing walking bouts, steps, sitting periods and transfers. Stair climbing events or similar activities such as walking steep slopes were classified using the higher mean hip flexion angle as a feature.


Orthopaedic Proceedings
Vol. 99-B, Issue SUPP_9 | Pages 60 - 60
1 May 2017
Alizai M Lipperts M Houben R Heyligers I Grimm B
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Background

To complement subjective patient-reported outcome measures, objective assessments are needed. Activity is an objective clinical outcome which can be measured with wearable activity monitors (AM). AM's have been validated and used in joint arthroplasty patients to count postures, walking or transfers. However, for demanding patients such as after sports injury, running is an important activity to quantify. A new AM algorithm to distinguish walking from running is trialed in this validation study.

Methods

Test subjects (n=9) performed walking and running bouts of 30s duration on a treadmill at fixed speeds (walking: 3, 4, 5, 7km/h, running: 5, 7, 9, 12, 15km/h) and individually preferred speeds (slow, normal, fast, maximum, walk/run transition). Flat and inclined surfaces (8%, 16%), different footwear (soft, hard, barefoot) and running styles (hind/fore-foot) were tested. An AM (3D accelerometer) was worn on the lateral thigh. Previously validated algorithms to classify all gait as walking were adapted to differentiate running from walking, the main criterium being vertical acceleration peaks exceeding 2g within each subsequent 2s-interval. Independently annotated video observation served as reference.


Orthopaedic Proceedings
Vol. 99-B, Issue SUPP_1 | Pages 10 - 10
1 Jan 2017
Buil I Ahmadinezhad S Göertz Y Lipperts M Heyligers I Grimm B
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Besides eliminating pain, restoring activity is a major goal in orthopaedic interventions including joint replacement or trauma surgery following falls in frail elderly, both treatments of highest socio-economic impact.

In joint replacement and even more so in frail elderly at risk of falling, turns are assessed in clinical tests such as the TUG (Timed Get-up-and-Go), Tinetti, or SPPB so that classifying turning movements in the free field with wearable activity monitors promises clinically valuable objective diagnostic or outcome parameters.

It is the aim of this study to validate a computationally simple turn detection algorithm for a leg-worn activity monitor comprising 3D gyroscopes.

A previously developed and validated activity classification algorithm for thigh-worn accelerometers was extended by adding a turn detection algorithm to its decision tree structure and using the 3D gyroscope of a new 9-axis IMU (56×40×15mm, 25g, f=50Hz,).

Based on published principles (El-Gohary et al. Sensors 2014), the turn detection algorithm filters the x-axis (thigh) for noise and walking (Butterworth low-pass, 2ndorder with a cut-off at 4Hz and 4thorder with a cut-off at 0.3Hz) before using a rotational speed threshold of 15deg/s to identify a turn and taking the bi-lateral zero-crossings as start and stop markers to integrate the turning angle.

For validation, a test subject wore an activity monitor on both thighs and performed a total of 57 turns of various types (walking, on-the-spot, fast/slow), ranges (45 to 360deg) and directions (left/right) in free order while being video-taped. An independent observer annotated the video so that the algorithmic counts could be compared to n=114 turns. Video-observation was compared to the algorithmic classification in a confusion matrix and the detection accuracy (true positives) was calculated.

In addition, 4-day continuous activity measures from 4 test subjects (2 healthy, 2 frail elderly) were compared.

Overall, only 5/114 turns were undetected producing a 96% detection accuracy. No false positives were classified. However, when detection accuracy was calculated for turning angle intervals (45°: 30–67.5°; 90°: 67.5–135°; 180°: 135–270°; 360°: 270–450°), accuracy for all interval classifications combined dropped to 83.3% with equal values for left and right turns. For the 180° and 360°, accuracy was 100% while for the shorter 45° and 90° turns accuracy was 75% and 71% only, mainly because subsequent turns were not separated.

Healthy subjects performed between 470 (office worker) and 823 (house wife) turns/day while frail elderly scored 128 (high fall risk) to 487 turns/day (low fall risk). Turns/day and steps/day were not correlated. In healthy subjects ca. 50% of turns were in the 45° category compared to only ca. 35% in frail elderly.

Turn detection for a thigh-worn IMU activity monitor using a computationally simple algorithm is feasible with high general detection accuracy. The classification and separation of subsequent short turns can be further improved.

In multi-day measurement, turns/day and the distribution of short and long turns seem to be a largely independent activity parameter compared to step counts and may improve objective assessment of fall risk or arthroplasty outcome.


Orthopaedic Proceedings
Vol. 99-B, Issue SUPP_1 | Pages 66 - 66
1 Jan 2017
Reeder I Lipperts M Heyligers I Grimm B
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Eliminating pain and restoring physical activity are the main goals of total hip arthroplasty (THA). Despite the high relevance of activity as a rehabilitation goal of and criterion for discharge, in-hospital activity between operation and discharge has hardly been investigated in orthopaedic patients.

Therefore, the aim of this study was to a) measure for reference the level of in-hospital physical activity in patient undergoing a current rapid discharge protocol, b) compare these values to a conventional discharge protocol and c) test correlations with pre-operative activities and self-reported outcomes for possible predictors for rapid recovery and discharge.

Patients (n=19, M:F: 5:14, age 65 ±5.7 years) with osteoarthritis treated with an elective primary THA underwent a rapid recovery protocol with discharge on day 3 after surgery (day 0). Physical activity was measured using a 3D accelerometer (64×25×13mm, 18g) worn on laterally on the unaffected upper leg. The signal was analysed using self-developed, validated algorithms (Matlab) calculating: Time on Feet (ToF), steps, sit-stand-transfers (SST), mean cadence (steps/min), walking bouts, longest walk (steps).

For the in-hospital period (am: ca. 8–13h; pm: ca. 13–20h) activity was calculated for day 1 (D1) and 2 (D2). Pre-operative activity at home was reported as the daily averages of a 4-day period. Patient self-report included the HOOS, SQUASH (activity) and Forgotten Joint Score (FJS) questionnaires.

In-hospital activity of this protocol was compared to previously collected data of an older (2011), standard conventional discharge protocol (day 4/5, n=40, age 71 ±7 years, M:F 16:24).

All activity parameters increased continuously between in-hospital days and subsequent am and pm periods. E.g. Time-on-feet increased most steeply and tripled from 21.6 ±14.4min at D1am to 62.6 ±33.4min at D2pm. Mean Steps increased almost as steep from 252 to 655 respectively. SST doubled from 4.9 to 10.5. All these values were sign. higher (+63 to 649%) than the conventional protocol data.

Cadence as a qualitative measure only increased slowly (+22%) (34.8 to 42.3steps/min) equalling conventional protocol values. The longest walking bout did not increase during the in-hospital period. Gender, age and BMI had no influence on in-hospital activity.

High pre-op activity (ToF, steps) was a predictor for high in-hospital activity for steps and SST's at D2pm (R=0.508 to R=0.723). Pre-op self-report was no predictor for any activity parameter.

In-hospital recovery of activity is steep following a cascade of easy (ToF) to demanding (SST) tasks to quality (cadence). High standard deviations show that recovering activity is highly individual possibly demanding personalised support or goals (feedback).

Quantitative parameters were all higher in the rapid versus the conventional discharge protocol indicating that fast activation is possible and safe. Equal cadence for both protocols shows that functional capacity cannot be easily accelerated.

Pre-op activity is only a weak predictor of in-hospital recovery, indicating that surgical trauma affects patients similarly, but subjects may be identified for personalized physiotherapy or faster discharge.

Reference values and correlations from this study can be used to optimize or shorten in-hospital rehabilitation via personalization, pre-hab, fast-track surgery or biofeedback.


Orthopaedic Proceedings
Vol. 99-B, Issue SUPP_1 | Pages 1 - 1
1 Jan 2017
Reeder I Lipperts M Heyligers I Grimm B
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Introduction: Physical activity is a major outcome in total hip arthroplasty (THA) and discharge criterion. Increasing immediate post-op activity may accelerate discharge, enable fast track surgery and improve general rehabilitation. Preliminary evidence (O'Halloran P.D. et al. 2015) shows that feedback via motivational interviewing can result in clinically meaningful improvements of physical activity. It was the aim of this study to use wearable sensor activity monitors to provide and study the effect of biofeedback on THA patients' activity levels. It was hypothesized that biofeedback would increase in-hospital and post-discharge activity versus controls.

Methods: In this pilot study, 18 patients with osteoarthritis receiving elective primary THA followed by a rapid recovery protocol with discharge on day 3 after surgery (day 0) were randomized to the feedback group (n=9, M/F: 4:5, age 63.3 ± 5.9 years, BMI 26.9 ± 5.1) or a non-feedback control group (n=9, M/F: 0:9, age 66.9 ± 5.1 years, BMI 27.1 ± 4.0). Physical activity was measured using a wearable sensor and parameters (Time-on-Feet (ToF), steps, sit-stand-transfers (SST), mean cadence (steps/min)) were calculated using a previously validated algorithms (Matlab). For the in-hospital period data was calculated twice daily (am, ca. 8–13:00h and pm, ca. 13–20:00h) of day 1 (D1) and 2 (D2). The feedback group had parameters reported back twice (morning, lunch) using bar charts comparing visually and numerically their values (without motivational instructions) to a previously measured reference group (n=40, age 71 ±7 years, M:F 16:24) of a conventional discharge protocol (day 4/5). Activity measures continued from discharge (D3) until day 5 (D5) at home.

Results: Randomization resulted in matched groups regarding age and BMI, but not gender. The first post-op activity assessment (D1am) was identical between groups. Also thereafter similar values with no significant differences in any parameter were seen, e.g. the time-on-feet at D2PM was 59.2 ±31.7min (feedback) versus 62.9 ±39.2min (controls). Also on the day of discharge and beyond, no effect from the in-hospital feedback was measured. For both groups the course of activity recovery showed a distinct drop on day 4 following a highly active day of discharge (D3). On day 5, activity levels only recovered partially. For both groups, all quantitative activity parameters were significantly higher than the reference values used for feedback. Only cadence as a qualitative measure was the same like reference values.

Discussion: Biofeedback using activity values from a body-worn monitor did not increase in-hospital or immediate post-op home activity levels compared to a control group when using the investigated feedback protocol. In general, while the day of discharge steeply boosts patient activity, the day after at home results in an activity drop to near in-patient levels before discharge. In a fast track surgery protocol, it may be of value to avoid this drop via patient education or home physiotherapy. Biofeedback using activity monitors to increase immediate post-op activity for fast track surgery or improved recovery may only be effective when feedback goals are set higher, are personalised or have additional motivational context.


Orthopaedic Proceedings
Vol. 98-B, Issue SUPP_8 | Pages 8 - 8
1 May 2016
Grimm B Lipperts M Senden R
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Introduction

The goal of total hip arthroplasty (THA) is to reduce pain, restore function but also activity levels for general health benefits or social participation. Thus evaluating THA patient activity can be important for diagnosis, indication, outcome assessment or biofeedback.

Methods

Physical activity (PA) of n=100 primary THA patients (age at surgery 63 ±8yrs; 49M/51F; 170 ±8cm, 79.8 ±14.0kg) was measured at 8 ±3yrs follow-up. A small 3D accelerometer was worn for 4 successive days during waking hours at the non-affected lateral upper leg. Data was analyzed using validated algorithms (Matlab) producing quantitative (e.g. #steps, #transfers, #walking bouts) and qualitative (e.g. cadence, temporal distribution of events) activity parameters. An age matched healthy control group (n=40, 69 ±8yrs, 22M/18F) served as reference.


Orthopaedic Proceedings
Vol. 98-B, Issue SUPP_8 | Pages 9 - 9
1 May 2016
Grimm B Moonen M Lipperts M Heyligers I
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Introduction

Unicompartmental knee arthroplasty is in particular promoted for knee OA patients with high demands on function and activity. This study used wearable inertial sensors to objectively assess function during specific motion tasks and to monitor activities of daily living to verify if UKA permits better function or more activity in particular with demanding tasks.

Methods

In this retrospective, cross-sectional study, UKA patients (Oxford, n=26, 13m/13f, age at FU: 66.5 ±7.6yrs) were compared to TKA patients (Vanguard, n=26, 13m/13f, age: 66.0 ±6.9yrs) matched for gender, age and BMI (29.5 ±4.6) at 5 years follow-up.

Subjective evaluation of pain, function, physical activity and awareness of the joint arthroplasty was performed by means of four PROMs: VAS pain, KOOS-PS, SQUASH (activity) and Forgotten Joint Score (FJS),

Objective measurement of function was performed using a 3D inertia sensor attached to the sacrum while performing gait test, sit-stand and block-step tests. To derive functional parameters such as walking cadence or sway during transfers or step-up previously validated algorithms were used (Bolink et al., 2012).

Daily physical activity was objectively monitored with a 3D accelerometer attached to the lateral side of the unaffected upper leg during four consecutive days. Activity parameters (counts and times of postures, steps, stairs, transfers, etc.) were also derived using validated algorithms. Data was analysed using independent T-test, Mann-Whitney U test and Pearson's correlation.


Orthopaedic Proceedings
Vol. 95-B, Issue SUPP_9 | Pages 26 - 26
1 Feb 2013
Brunton L Bolink S van Laarhoven S Lipperts M Grimm B Heyligers I Blom A
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Accelerometer based gait analysis (AGA) is a potential alternative to the more commonly used skin marker based optical motion analysis system(OMAS). The use of gyroscopes in conjunction with accelerometers (i.e. inertial sensors), enables the assessment of position and angular movements of body segments and provides ambulatory kinematic characterisation of gait.

We investigated commonly used gait parameters and also a novel parameter, Pelvic obliquity (PO) and whether they can be used as a parameter of physical function and correlate with classic clinical outcome scores

Gait was studied in healthy subjects (n=20), in patients with end stage hip OA (n=20) and in patients with end stage knee OA (n=20). Subjects walked 20 metres in an indoor environment along a straight flat corridor at their own preferred speed. A 3D inertial sensor was positioned centrally between the posterior superior iliac spines (PSIS) overlying S1.

Comparing gait parameters of end stage hip OA patients with an age and gender matched healthy control group, significantly lower walking speed, longer step duration and shorter step length was observed. After correcting for walking speed between groups, significantly less average range of motion of PO (RoMpo) was observed for patients with end stage hip OA compared to healthy subjects and patients with end stage knee OA.

IGA allows objective assessment of physical function for everyday clinical practice and allows assessment of functional parameters beyond time only. IGA measures another dimension of physical function and could be used supplementary to monitor recovery of OA patients after TJR.


Orthopaedic Proceedings
Vol. 94-B, Issue SUPP_XXXVII | Pages 193 - 193
1 Sep 2012
Lipperts M Grimm B Van Asten W Senden R Van Laarhoven S Heyligers I
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Introduction

In orthopaedics, clinical outcome assessment (COA) is still mostly performed by questionnaires which suffer from subjectivity, a ceiling effect and pain dominance. Real life activity monitoring (AM) holds the promise to become the new standard in COA with small light weight and easy to use accelerometers. More and more activities can be identified by algorithms based on accelerometry. The identification of stair climbing for instance is important to assess the participation of patients in normal life after an orthopaedic procedure. In this study we validated a custom made algorithm to distinguish normal gait, ascending and descending stairs on a step by step basis.

Methods

A small, lightweight 3D-accelerometer taped to the lateral side of the affected (patients) or non-dominant (healthy subjects) upper leg served as the activity monitor. 13 Subjects (9 patients, 4 healthy) walked a few steps before descending a flight stairs (20 steps with a 180o turn in the middle), walked some steps more, turned around and ascended the same stairs. Templates (up, down and level) were obtained by averaging and stretching the vertical acceleration in the 4 healthy subjects. Classification parameters (low pass (0.4 Hz) horizontal (front-back) acceleration and the Euclidian distance between the vertical acceleration and each template) were obtained for each step. Accuracy is given by the percentage of correctly classified steps.


Orthopaedic Proceedings
Vol. 94-B, Issue SUPP_XXXVII | Pages 235 - 235
1 Sep 2012
Lipperts M Senden R Van Asten W Heyligers I Grimm B
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Introduction

In orthopaedics, clinical outcome assessment (COA) is mostly performed by questionnaires which suffer from subjectivity, a ceiling effect and pain dominance. Real life activity monitoring (AM) can objectively assess function and becomes now feasible as technology has become smaller, lighter, cheaper and easier to use. In this study we validated a custom made algorithm based on accelerometry using different orthopaedic patients with the aim to use AM in orthopaedic COA.

Methods

A small, lightweight 3D-accelerometer taped to the lateral side of the affected upper leg served as the activity monitor. AM algorithms were programmed in Matlab to classify standing, sitting, and walking. For validation a common protocol was used; subjects were asked to perform several tasks for 5 or 10 seconds in a fixed order. An observer noted the starting time of each task using a stopwatch.

Accuracy was calculated for the number of bouts per activity as well as total time per activity. 10 Subjects were chosen with different pathologies (e.g. post total knee/hip arthroplasty, osteoarthritis) since the difference in movement dynamics in each pathology poses a challenge to the algorithm.