Estimation and visualization of sagittal kinematics of lower limbs orientation using body-fixed sensors

Examination of a practical method to quantitatively evaluate the rolling over movement in a clinical setting

[Purpose] We investigated the utility of wearable inertial and magnetic sensing modules for analyzing neck and trunk movements during the rolling over movement. [Participants and Methods] The participants were instructed to roll over from the supine to the side-lying position with three sensor units attached to their forehead, xiphoid process of the sternum, and abdomen. Experiments were conducted on two prescribed patterns: one emphasizing hip joint flexion and adduction, and the other focusing on scapular protraction and horizontal shoulder joint adduction in two healthy participants (one male and one female). The flexion and rotation angles of the neck and trunk were calculated using conventional spreadsheet software with data obtained from the sensors. The obtained values were compared for agreement with those derived from a three-dimensional (3D) motion analysis device. [Results] The cross-correlation coefficient for the flexion and rotation angles of the neck and trunk between the two measurement methods was approximately 0.85, and the root mean square (RMS) angle difference was approximately 5.0°. [Conclusion] Wearable inertial and magnetic sensors can be used to quantitatively evaluate neck and trunk movements during the rolling over movement.

A machine-learning method isolating changes in wrist kinematics that identify age-related changes in arm movement

Normal aging often results in an increase in physiological tremors and slowing of the movement of the hands, which can impair daily activities and quality of life. This study, using lightweight wearable non-invasive sensors, aimed to detect and identify age-related changes in wrist kinematics and response latency. Eighteen young (ages 18-20) and nine older (ages 49-57) adults performed two standard tasks with wearable inertial measurement units on their wrists. Frequency analysis revealed 5 kinematic variables distinguishing older from younger adults in a postural task, with best discrimination occurring in the 9-13 Hz range, agreeing with previously identified frequency range of age-related tremors, and achieving excellent classifier performance (0.86 AUROC score and 89% accuracy). In a second pronation-supination task, analysis of angular velocity in the roll axis identified a 71 ms delay in initiating arm movement in the older adults. This study demonstrates that an analysis of simple kinematic variables sampled at 100 Hz frequency with commercially available sensors is reliable, sensitive, and accurate at detecting age-related increases in physiological tremor and motor slowing. It remains to be seen if such sensitive methods may be accurate in distinguishing physiological tremors from tremors that occur in neurological diseases, such as Parkinson's Disease.

Reliability and validity of estimated angles information assessed using inertial measurement unit-based motion sensors

BACKGROUND

Inertial measurement unit (IMU)-based motion sensors are affordable, and their use is appropriate for rehabilitation. However, regarding the accuracy of estimated angle information obtained from this sensor, it is reported that it is likely affected by velocity.

OBJECTIVE

The present study investigated the reliability and validity of the angle information obtained using IMU-based sensors compared with a three-dimensional (3D) motion analyzer.

METHODS

The Euler angle obtained using the 3D motion analyzer and the angle obtained using the IMU-based sensor (IMU angle) were compared. Reliability was assessed by comparing the Bland-Altman analysis, intra-class correlation coefficient (ICC) (1,1), and cross-correlation function. The root mean square (RMS) error, ICC (2,1), and cross-correlation function were used to compare data on the Euler and IMU angles to evaluate the validity.

RESULTS

Regarding reliability, the Bland-Atman analysis indicated no fixed or proportional bias in the angle measurements. The measurement errors ranged from 0.2° to 3.2°. In the validity, the RMS error ranged from 0.3° to 2.2°. The ICCs (2,1) were 0.9. The cross-correlation functions were >0.9, which indicated a high degree of agreement.

CONCLUSION

The IMU-based sensor had a high reliability and validity. The IMU angle may be used in rehabilitation.

NONAN GaitPrint: An IMU gait database of healthy young adults

An ongoing thrust of research focused on human gait pertains to identifying individuals based on gait patterns. However, no existing gait database supports modeling efforts to assess gait patterns unique to individuals. Hence, we introduce the Nonlinear Analysis Core (NONAN) GaitPrint database containing whole body kinematics and foot placement during self-paced overground walking on a 200-meter looping indoor track. Noraxon Ultium MotionTM inertial measurement unit (IMU) sensors sampled the motion of 35 healthy young adults (19-35 years old; 18 men and 17 women; mean ± 1 s.d. age: 24.6 ± 2.7 years; height: 1.73 ± 0.78 m; body mass: 72.44 ± 15.04 kg) over 18 4-min trials across two days. Continuous variables include acceleration, velocity, position, and the acceleration, velocity, position, orientation, and rotational velocity of each corresponding body segment, and the angle of each respective joint. The discrete variables include an exhaustive set of gait parameters derived from the spatiotemporal dynamics of foot placement. We technically validate our data using continuous relative phase, Lyapunov exponent, and Hurst exponent-nonlinear metrics quantifying different aspects of healthy human gait.

Estimation of Lower Limb Joint Angles and Joint Moments during Different Locomotive Activities Using the Inertial Measurement Units and a Hybrid Deep Learning Model

Using inertial measurement units (IMUs) to estimate lower limb joint kinematics and kinetics can provide valuable information for disease diagnosis and rehabilitation assessment. To estimate gait parameters using IMUs, model-based filtering approaches have been proposed, such as the Kalman filter and complementary filter. However, these methods require special calibration and alignment of IMUs. The development of deep learning algorithms has facilitated the application of IMUs in biomechanics as it does not require particular calibration and alignment procedures of IMUs in use. To estimate hip/knee/ankle joint angles and moments in the sagittal plane, a subject-independent temporal convolutional neural network-bidirectional long short-term memory network (TCN-BiLSTM) model was proposed using three IMUs. A public benchmark dataset containing the most representative locomotive activities in daily life was used to train and evaluate the TCN-BiLSTM model. The mean Pearson correlation coefficient of joint angles and moments estimated by the proposed model reached 0.92 and 0.87, respectively. This indicates that the TCN-BiLSTM model can effectively estimate joint angles and moments in multiple scenarios, demonstrating its potential for application in clinical and daily life scenarios.

A convenient approach for knee kinematics assessment using wearable inertial sensors during home-based rehabilitation: Validation with an optoelectronic system

Rehabilitation services are among the most severely impacted by the COVID-19 pandemic. This has increased the number of people not receiving the needed rehabilitation care. Home-based rehabilitation becomes alternative support to face this greater need. However, monitoring kinematics parameters during rehabilitation exercises is critical for an effective recovery. This work proposes a detailed framework to estimate knee kinematics using a wearable Magnetic and Inertial Measurement Unit (MIMU). That allows at-home monitoring for knee rehabilitation progress. Two MIMU sensors were attached to the shank and thigh segments respectively. First, the absolute orientation of each sensor was estimated using a sensor fusion algorithm. Second, these sensor orientations were transformed to segments orientations using a functional sensor-to-segment (STS) alignment. Third, the relative orientation between segments, i.e., knee joint angle, was computed and the relevant kinematics parameters were extracted. Then, the validity of our approach was evaluated with a gold-standard optoelectronic system. Seven participants completed three to five Timed-Up-and-Go (TUG) tests. The estimated knee angle was compared to the reference angle. Root-mean-square error (RMSE), correlation coefficient, and Bland-Altman analysis were considered as evaluation metrics. Our results showed reasonable accuracy (RMSE < 8°), strong to very-strong correlation (correlation coefficient > 0.86), a mean difference within 1.1°, and agreement limits from -16° to 14°. In addition, no significant difference was found (p-value > 0.05) in extracted kinematics parameters between both systems. The proposed approach might represent a suitable alternative for the assessment of knee rehabilitation progress in a home context.

Ten-year follow-up of a total knee prosthesis combining multi-radius, ultra-congruency, posterior-stabilization and mobile-bearing insert shows long-lasting clinically relevant improvements in pain, stiffness, function and stability

PURPOSE

There is a paucity of data available on total knee prostheses combining dual-radius, ultra-congruency, posterior-stabilization and mobile-bearing insert. This prospective cohort study aimed to assess the clinical evolution of the FIRST^® prosthesis (Symbios Orthopédie, Yverdon, CH), the earliest prosthesis with this particular design. It was hypothesized that the primary outcomes, evaluating pain, stiffness, function and stability, would improve following arthroplasty and remain improved during the follow-up period of 10 years.

METHODS

All patients programmed for a total knee arthroplasty using a FIRST^® prosthesis at our university hospital between 2006 and 2008 were invited to participate. Study knees were evaluated pre-operatively as well as one, five and ten years post-operatively. Patients filled out questionnaires at each evaluation point and had a radiographic assessment at the five-year and ten-year follow-ups. Primary outcomes were the total, pain, stiffness and function measures of the Western Ontario and McMaster Universities Osteoarthritis questionnaire (WOMAC) and the knee and function measures of the Knee Society Score (KSS). Friedman and Wilcoxon's rank-sum tests were used to compare measures across time points.

RESULTS

Hundred and twenty four prostheses were included (baseline demographics: 69.9 ± 8.3 years old, 28.1 ± 4.3 kg/m², 54% male) and 68 could be followed during ten years. Five prostheses underwent a revision. All other prostheses lost at follow-up were lost for reasons unrelated to the prosthesis. All primary measures reported statistically and clinically significant improvements between baseline and the three follow-up evaluations. Statistically significant improvements at the three follow-up evaluations were also observed for most secondary measures. There was no implant loosening. At ten-year follow-up, radiolucent lines were observed in 2.9% femoral implants and 1.5% tibial implants.

CONCLUSION

The positive results observed in all domains of assessment and the small revision rate demonstrated an effective functioning of the FIRST^® prosthesis during the ten-year follow-up period. The results, globally similar to those previously published for other prosthesis designs, encourage the development of assistive methods to select the most appropriate designs on an individual basis.

LEVEL OF EVIDENCE

IV, prospective cohort study.

Frontal Plane Neurokinematic Mechanisms Stabilizing the Knee and the Pelvis during Unilateral Countermovement Jump in Young Trained Males

(1) The unilateral countermovement jump is commonly used to examine frontal plane kinetics during unilateral loading and to identify athletes with an increased risk of lower limb injuries. In the present study, we examined the biomechanical mechanisms of knee and pelvis stabilization during unilateral vertical jumps. (2) Healthy males performed jumps on a force plate with the dominant leg. Activity of the dominant-side gluteus medius and the contralateral-side quadratus lumborum and erector spinae muscles was recorded with surface EMG. The EMG data were normalized to the EMG activity recorded during maximal voluntary isometric hip abduction and lateral trunk flexion contractions. During jumps, the propulsive impulse was measured, and the pelvis and thigh segmental orientation angles in the frontal plane were recorded and synchronized with the EMG data. (3) The magnitude of knee valgus during the jump did not correlate with hip abduction force, but negatively correlated with gluteus medius activity. This correlation became stronger when gluteus medius activity was normalized to hip abduction force. Propulsive impulse did not correlate with any neuromechanical measurement. (4) We conclude that hip abduction force itself does not regulate the magnitude of knee valgus during unilateral jumps; rather, the gluteus medius should be highly activated to increase frontal-plane knee joint stability.

A novel approach for modelling and classifying sit-to-stand kinematics using inertial sensors

Sit-to-stand transitions are an important part of activities of daily living and play a key role in functional mobility in humans. The sit-to-stand movement is often affected in older adults due to frailty and in patients with motor impairments such as Parkinson's disease leading to falls. Studying kinematics of sit-to-stand transitions can provide insight in assessment, monitoring and developing rehabilitation strategies for the affected populations. We propose a three-segment body model for estimating sit-to-stand kinematics using only two wearable inertial sensors, placed on the shank and back. Reducing the number of sensors to two instead of one per body segment facilitates monitoring and classifying movements over extended periods, making it more comfortable to wear while reducing the power requirements of sensors. We applied this model on 10 younger healthy adults (YH), 12 older healthy adults (OH) and 12 people with Parkinson's disease (PwP). We have achieved this by incorporating unique sit-to-stand classification technique using unsupervised learning in the model based reconstruction of angular kinematics using extended Kalman filter. Our proposed model showed that it was possible to successfully estimate thigh kinematics despite not measuring the thigh motion with inertial sensor. We classified sit-to-stand transitions, sitting and standing states with the accuracies of 98.67%, 94.20% and 91.41% for YH, OH and PwP respectively. We have proposed a novel integrated approach of modelling and classification for estimating the body kinematics during sit-to-stand motion and successfully applied it on YH, OH and PwP groups.

Validation of wearable inertial sensor-based gait analysis system for measurement of spatiotemporal parameters and lower extremity joint kinematics in sagittal plane

Wearable inertial sensor-based motion analysis systems are promising alternatives to standard camera-based motion capture systems for the measurement of gait parameters and joint kinematics. These wearable sensors, unlike camera-based gold standard systems, find usefulness in outdoor natural environment along with confined indoor laboratory-based environment due to miniature size and wireless data transmission. This study reports validation of our developed (i-Sens) wearable motion analysis system against standard motion capture system. Gait analysis was performed at self-selected speed on non-disabled volunteers in indoor ( n = 15) and outdoor ( n = 8) environments. Two i-Sens units were placed at the level of knee and hip along with passive markers (for indoor study only) for simultaneous 3D motion capture using a motion capture system. Mean absolute percentage error (MAPE) was computed for spatiotemporal parameters from the i-Sens system versus the motion capture system as a true reference. Mean and standard deviation of kinematic data for a gait cycle were plotted for both systems against normative data. Joint kinematics data were analyzed to compute the root mean squared error (RMSE) and Pearson’s correlation coefficient. Kinematic plots indicate a high degree of accuracy of the i-Sens system with the reference system. Excellent positive correlation was observed between the two systems in terms of hip and knee joint angles (Indoor: hip 3.98° ± 1.03°, knee 6.48° ± 1.91°, Outdoor: hip 3.94° ± 0.78°, knee 5.82° ± 0.99°) with low RMSE. Reliability characteristics (defined using standard statistical thresholds of MAPE) of stride length, cadence, walking speed in both outdoor and indoor environment were well within the “Good” category. The i-Sens system has emerged as a potentially cost-effective, valid, accurate, and reliable alternative to expensive, standard motion capture systems for gait analysis. Further clinical trials using the i-Sens system are warranted on participants across different age groups.

An Integrated Multimodal Knee Brace Enabling Mid-Activity Tracking for Joint Health Assessment

Developments in wearable technologies created opportunities for non-invasive joint health assessment while subjects perform daily activities during rehabilitation and recovery. However, existing state-of-art solutions still require a health professional or a researcher to set up the device, and most of them are not convenient for at-home use. In this paper, we demonstrate the latest version of the multimodal knee brace that our lab previously developed. This knee brace utilizes four sensing modalities: joint acoustic emissions (JAEs), electrical bioimpedance (EBI), activity and temperature. We designed custom printed-circuit boards and developed firmware to acquire high quality data. For the brace material, we used a commercial knee brace and modified it for the comfort of patients as well as to secure all electrical connections. We updated the electronics to enable rapid EBI measurements for mid-activity tracking. The performance of the multimodal knee brace was evaluated through a proof-of-concept human subjects study (n=9) with 2 days of measurement and 3 sessions per day. We obtained consistent EBI data with less than 1 Ω variance in measured impedance within six full frequency sweeps (each sweep is from 5 kHz to 100 kHz with 256 frequency steps) from each subject. Then, we asked subjects to perform 10 unloaded knee flexion/extensions, while we measured continuous 5 kHz and 100 kHz EBI at every 100 ms. The ratio of the range of reactance (ΔX_5kHz/ΔX100kHz) was found to be less than 1 for all subjects for all cycles, which indicates lack of swelling and thereby a healthy joint. We also conducted intra and inter session reliability analysis for JAE recordings through intraclass correlation analysis (ICC), and obtained excellent ICC values (>0.75), suggesting reliable performance on JAE measurements. The presented knee brace could readily be used at home in future work for knee health monitoring of patients undergoing rehabilitation or recovery.

The Protraction and Retraction Angles of Horse Limbs: An Estimation during Trotting Using Inertial Sensors

The protraction and retraction angles of horse limbs are important in the analysis of horse locomotion. This study explored two methods from an IMU positioned on the canon bone of eight horses to estimate these angles. Each method was based on a hypothesis in order to define the moment corresponding with the verticality of the canon bone: (i) the canon bone is in a vertical position at 50% of the stance phase or (ii) the verticality of the canon bone corresponds with the moment when the horse’s withers reach their lowest point. The measurements were carried out on a treadmill at a trot and compared with a standard gold method based on motion capture. For the measurement of the maximum protraction and retraction angles, method (i) had average biases (0.7° and 1.7°) less than method (ii) (−1.3° and 3.7°). For the measurement of the protraction and retraction angles during the stance phase, method (i) had average biases (4.1° and −3.3°) higher to method (ii) (2.1° and −1.3°). This study investigated the pros and cons of a generic method (i) vs. a specific method (ii) to determine the protraction and retraction angles of horse limbs by a single IMU.

Estimation of 3D Body Center of Mass Acceleration and Instantaneous Velocity from a Wearable Inertial Sensor Network in Transfemoral Amputee Gait: A Case Study

The analysis of the body center of mass (BCoM) 3D kinematics provides insights on crucial aspects of locomotion, especially in populations with gait impairment such as people with amputation. In this paper, a wearable framework based on the use of different magneto-inertial measurement unit (MIMU) networks is proposed to obtain both BCoM acceleration and velocity. The proposed framework was validated as a proof of concept in one transfemoral amputee against data from force plates (acceleration) and an optoelectronic system (acceleration and velocity). The impact in terms of estimation accuracy when using a sensor network rather than a single MIMU at trunk level was also investigated. The estimated velocity and acceleration reached a strong agreement (ρ > 0.89) and good accuracy compared to reference data (normalized root mean square error (NRMSE) < 13.7%) in the anteroposterior and vertical directions when using three MIMUs on the trunk and both shanks and in all three directions when adding MIMUs on both thighs (ρ > 0.89, NRMSE ≤ 14.0% in the mediolateral direction). Conversely, only the vertical component of the BCoM kinematics was accurately captured when considering a single MIMU. These results suggest that inertial sensor networks may represent a valid alternative to laboratory-based instruments for 3D BCoM kinematics quantification in lower-limb amputees.

Instrumented triple single-leg hop test: A validated method for ambulatory measurement of ankle and knee angles using inertial sensors

BACKGROUND

Hop tests are commonly used in clinical environments to measure function after sport-related knee injuries. Joint angle measurement during hopping is feasible in research-based environments equipped with motion-capture systems. Employing these systems in clinical research settings is inefficient, given the associated cost, preparation time, and expertise required to administer and interpret the findings. Therefore, this study aimed to introduce a wearable system comprising three inertial measurement units for 3D joint angular measurement during horizontal hop tests, validate the joint angles against a camera-based system, and evaluate its applicability in clinical research environments.

METHODS

Ten able-bodied participants were outfitted with three inertial measurement units during triple single-leg hop trials. 3D knee and ankle angles were calculated using the strap-down integration method, and results were compared with camera-based joint angles. Additionally, knee and ankle range of motions (RoMs) during bilateral triple single-leg hop trials were compared for 22 participants with unilateral sport-related knee injuries and 10 uninjured participants.

FINDINGS

Estimated angles had root-mean-square and RoM error medians of less than 2.3 and 3.2 degrees for both joints, and correlation coefficients of above 0.92 when compared with the camera-based system, for all hop phases. Injured participants had smaller sagittal ankle RoM (P = .008) on their injured side, during the third hop. Concurrently, they demonstrated smaller knee RoM symmetry indices (P = .017) and injured knee sagittal RoMs (P = .009) compared to uninjured participants.

INTERPRETATION

The introduced system had appropriate accuracy to highlight post-injury modifications in hopping kinematics and reveal noteworthy differences in RoM of clinical samples.

Cathodal Cerebellar tDCS Combined with Visual Feedback Improves Balance Control

Balance control is essential to maintain a stable body position and to prevent falls. The aim of this study was to determine whether balance control could be improved by using cerebellar transcranial direct current stimulation (tDCS) and visual feedback in a combined approach. A total of 90 healthy volunteers were randomly assigned to six groups defined by the delivery of tDCS (cathodal or anodal or sham) and the provision or not of visual feedback on balance during the acquisition phase. tDCS was delivered over the cerebellar hemisphere ipsilateral to the dominant leg for 20 min at 2 mA during a unipedal stance task. Body sway (i.e., ankle angle and hip position) was measured as an overall maximal unit in anteroposterior and mediolateral direction, together with participant rating of perception of stability, before (baseline), during (acquisition), and after (final) the intervention. We found a reduction in body sway during the acquisition session when visual feedback alone was provided. When the visual feedback was removed (final session), however, body sway increased above baseline. Differently, the reduction in overall maximal body sway was maintained during the final session when the delivery of cathodal tDCS and visual feedback was combined. These findings suggest that cathodal tDCS may support the short-term maintenance of the positive effects of visual feedback on balance and provide the basis for a new approach to optimize balance control, with potential translational implications for the elderly and patients with impaired posture control.

IMU Sensor Fusion Algorithm for Monitoring Knee Kinematics in ACL Reconstructed Patients

In this paper we propose a sensor embedded knee brace to monitor knee flexion and extension and other lower limb joint kinematics after anterior cruciate ligament (ACL) injury. The system can be easily attached to a standard post-surgical brace and uses a novel sensor fusion algorithm that does not require calibration. The wearable system and the sensor fusion algorithm were validated for various physical therapy exercises against a validated motion capture system. The proposed sensor fusion algorithm demonstrated significantly lower root-mean-square error (RMSE) than the benchmark Kalman filtering algorithm and excellent correlation coefficients (CCC and ICC). The demonstrated error for most exercises was lower than other devices in the literature. The quantitative measures obtained by this system can be used to obtain longitudinal range-of-motion and functional biomarkers. These biomarkers can be used to improve patient outcomes through the early detection of at-risk patients, tracking patient function outside of the clinic, and the identification of relationships between patient presentation, intervention, and outcomes.

Gait Analysis in a Box: A System Based on Magnetometer-Free IMUs or Clusters of Optical Markers with Automatic Event Detection

Gait analysis based on full-body motion capture technology (MoCap) can be used in rehabilitation to aid in decision making during treatments or therapies. In order to promote the use of MoCap gait analysis based on inertial measurement units (IMUs) or optical technology, it is necessary to overcome certain limitations, such as the need for magnetically controlled environments, which affect IMU systems, or the need for additional instrumentation to detect gait events, which affects IMUs and optical systems. We present a MoCap gait analysis system called Move Human Sensors (MH), which incorporates proposals to overcome both limitations and can be configured via magnetometer-free IMUs (MH-IMU) or clusters of optical markers (MH-OPT). Using a test-retest reliability experiment with thirty-three healthy subjects (20 men and 13 women, 21.7 ± 2.9 years), we determined the reproducibility of both configurations. The assessment confirmed that the proposals performed adequately and allowed us to establish usage considerations. This study aims to enhance gait analysis in daily clinical practice.

Sensor-to-Segment Calibration Methodologies for Lower-Body Kinematic Analysis with Inertial Sensors: A Systematic Review

Kinematic analysis is indispensable to understanding and characterizing human locomotion. Thanks to the development of inertial sensors based on microelectronics systems, human kinematic analysis in an ecological environment is made possible. An important issue in human kinematic analyses with inertial sensors is the necessity of defining the orientation of the inertial sensor coordinate system relative to its underlying segment coordinate system, which is referred to sensor-to-segment calibration. Over the last decade, we have seen an increase of proposals for this purpose. The aim of this review is to highlight the different proposals made for lower-body segments. Three different databases were screened: PubMed, Science Direct and IEEE Xplore. One reviewer performed the selection of the different studies and data extraction. Fifty-five studies were included. Four different types of calibration method could be identified in the articles: the manual, static, functional, and anatomical methods. The mathematical approach to obtain the segment axis and the calibration evaluation were extracted from the selected articles. Given the number of propositions and the diversity of references used to evaluate the methods, it is difficult today to form a conclusion about the most suitable. To conclude, comparative studies are required to validate calibration methods in different circumstances.

Determining anatomical frames via inertial motion capture: A survey of methods

Despite the exponential growth in using inertial measurement units (IMUs) for biomechanical studies, future growth in "inertial motion capture" is stymied by a fundamental challenge - how to estimate the orientation of underlying bony anatomy using skin-mounted IMUs. This challenge is of paramount importance given the need to deduce the orientation of the bony anatomy to estimate joint angles. This paper systematically surveys a large number (N = 112) of studies from 2000 to 2018 that employ four broad categories of methods to address this challenge across a range of body segments and joints. We categorize these methods as: (1) Assumed Alignment methods, (2) Functional Alignment methods, (3) Model Based methods, and (4) Augmented Data methods. Assumed Alignment methods, which are simple and commonly used, require the researcher to visually align the IMU sense axes with the underlying anatomical axes. Functional Alignment methods, also commonly used, relax the need for visual alignment but require the subject to complete prescribed movements. Model Based methods further relax the need for prescribed movements but instead assume a model for the joint. Finally, Augmented Data methods shed all of the above assumptions, but require data from additional sensors. Significantly different estimates of the underlying anatomical axes arise both across and within these categories, and to a degree that renders it difficult, if not impossible, to compare results across studies. Consequently, a significant future need remains for creating and adopting a standard for defining anatomical axes via inertial motion capture to fully realize this technology's potential for biomechanical studies.

Drift-Free Foot Orientation Estimation in Running Using Wearable IMU

This study aimed to introduce and validate a new method to estimate and correct the orientation drift measured from foot-worn inertial sensors. A modified strap-down integration (MSDI) was proposed to decrease the orientation drift, which, in turn, was further compensated by estimation of the joint center acceleration (JCA) of a two-segment model of the foot. This method was designed to fit the different foot strike patterns observed in running and was validated against an optical motion-tracking system during level treadmill running at 8, 12, and 16 km/h. The sagittal and frontal plane angles obtained from the inertial sensors and the motion tracking system were compared at different moments of the ground contact phase. The results obtained from 26 runners showed that the foot orientation at mean stance was estimated with an accuracy (inter-trial median ± IQR) of 0.4 ± 3.8° and a precision (inter-trial precision median ± IQR) of 3.0 ± 1.8°. The orientation of the foot shortly before initial contact (IC) was estimated with an accuracy of 2.0 ± 5.9° and a precision of 1.6 ± 1.1°; which is more accurate than commonly used zero-velocity update methods derived from gait analysis and not explicitly designed for running. Finally, the study presented the effect initial and terminal contact (TC) detection errors have on the orientation parameters reported.

Comparison of a New Inertial Sensor Based System with an Optoelectronic Motion Capture System for Motion Analysis of Healthy Human Wrist Joints

This study aims to compare a new inertial measurement unit based system with the highly accurate but complex laboratory gold standard, an optoelectronic motion capture system. Inertial measurement units are sensors based on accelerometers, gyroscopes, and/or magnetometers. Ten healthy subjects were recorded while performing flexion-extension and radial-ulnar deviation movements of their right wrist using inertial sensors and skin markers. Maximum range of motion during these trials and mean absolute difference between the systems were calculated. A difference of 10° ± 5° for flexion-extension and 2° ± 1° for radial-ulnar deviation was found between the two systems with absolute range of motion values of 126° and 50° in the respective axes. A Wilcoxon rank sum test resulted in a no statistical differences between the systems with p-values of 0.24 and 0.62. The observed results are even more precise than reports from previous studies, where differences between 14° and 27° for flexion-extension and differences between 6° and 17° for radial-ulnar deviation were found. Effortless and fast applicability, good precision, and low inter-observer variability make inertial measurement unit based systems applicable to clinical settings.

Real Time Estimation of the Pose of a Lower Limb Prosthesis from a Single Shank Mounted IMU

The command of a microprocessor-controlled lower limb prosthesis classically relies on the gait mode recognition. Real time computation of the pose of the prosthesis (i.e., attitude and trajectory) is useful for the correct identification of these modes. In this paper, we present and evaluate an algorithm for the computation of the pose of a lower limb prosthesis, under the constraints of real time applications and limited computing resources. This algorithm uses a nonlinear complementary filter with a variable gain to estimate the attitude of the shank. The trajectory is then computed from the double integration of the accelerometer data corrected from the kinematics of a model of inverted pendulum rolling on a curved arc foot. The results of the proposed algorithm are evaluated against the optoelectronic measurements of walking trials of three people with transfemoral amputation. The root mean square error (RMSE) of the estimated attitude is around 3°, close to the Kalman-based algorithm results reported in similar conditions. The real time correction of the integration of the inertial measurement unit (IMU) acceleration decreases the trajectory error by a factor of 2.5 compared to its direct integration which will result in an improvement of the gait mode recognition.

Gait analysis following single-shot hyaluronic acid supplementation: a pilot randomized double-blinded controlled trial

Objectives

Viscosupplementation with new-generation, polyol-containing, cross-linked hyaluronic acid (HA) gels reduces joint inflammation in patients with knee osteoarthritis. Gait analysis is a complementary outcome measure to standard patient-reported scores and physical measures for testing the effect of HA injection. This three-arm, prospective, randomized, controlled, double-blind, feasibility pilot study investigated which gait parameters are more sensitive following a single bolus injection of polyol-containing HA for knee osteoarthritis.

Methods

Twenty-two patients with Ahlbäck grade II-III knee osteoarthritis were randomly allocated into three groups: (1) HA + mannitol (n = 9), (2) HA + sorbitol (n = 5), and (3) saline placebo (n = 8). Patients were assessed by blinded observers prior to injection and at 4 weeks post-injection (4W). Outcome measures included the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Knee Society score (KSS), EuroQol in five-dimensions (EQ-5D), VAS pain, and VAS stiffness. Gait was assessed over 30 m using a portable inertial-based data logger (Physilog®).

Results

Differences between 4W and baseline were statistically significant for the mannitol-containing viscosupplement, with a median increase of 0.076 m/s on gait speed (p = 0.039), 0.055 m on stride length (p = 0.027), and 15 points on the KSS (p = 0.047). In contrast, the HA + sorbitol and saline groups demonstrated no significant changes from baseline to 4W in any gait parameters or self-reported outcome measures (all p > 0.3). The observed increase in gait speed is approximately 13% greater than the mean difference between healthy subjects and those with knee osteoarthritis, is clinically important, and thus is a sensitive gait parameter.

Conclusions

This study demonstrated gait speed and stride length are the most relevant gait parameters to investigate when assessing the effect of polyol-containing HA viscosupplementation. This study supports the need for a larger, randomized, controlled, clinical trial to assess the effect of a single-bolus HA injection versus multiple injections in people with knee osteoarthritis using both gait performance and self-reported parameters of knee function.

Trial registration

This study was retrospectively registered at clinicaltrials.gov on August 20, 2018, and assigned #NCT03636971.

Level of evidence

I.

Positive verbal suggestion optimizes postural control

Balance is a very important function that allows maintaining a stable stance needed for many daily life activities and for preventing falls. We investigated whether balance control could be improved by a placebo procedure consisting of verbal suggestion. Thirty healthy volunteers were randomized in two groups (placebo and control) and asked to perform a single-leg stance task in which they had to stand as steadily as possible on the dominant leg. The task was repeated in three sessions (T0, T1, T2). At T1 and T2 an inert treatment was applied on the leg, by informing the placebo group that it was effective in improving balance. The control group was overtly told that treatment was inert. An accelerometer applied on participants’ leg allowed to measure body sways in different directions. Subjective parameters, like perception of stability, were also collected. Results showed that the placebo group had less body sways than the control group at T2, both in the three-dimensional space and in the anterior-posterior direction. Furthermore, the placebo group perceived to be more stable than the control group. This study represents the first evidence that placebo effect optimizes posture, with a potential translational impact in patients with postural and gait disturbances.

Validity of Wearable Sensors at the Shoulder Joint: Combining Wireless Electromyography Sensors and Inertial Measurement Units to Perform Physical Workplace Assessments

Background: Workplace adaptation is the preferred method of intervention to diminish risk factors associated with the development of work-related shoulder disorders. However, the majority of the workplace assessments performed are subjective (e.g., questionnaires). Quantitative assessments are required to support workplace adaptations. The aims of this study are to assess the concurrent validity of inertial measurement units (IMUs; MVN, Xsens) in comparison to a motion capture system (Vicon) during lifting tasks, and establish the discriminative validity of a wireless electromyography (EMG) system for the evaluation of muscle activity. Methods: Sixteen participants performed 12 simple tasks (shoulder flexion, abduction, scaption) and 16 complex lifting tasks (lifting crates of different weights at different heights). A Delsys Trigno EMG system was used to record anterior and middle deltoids’ EMG activity, while the Xsens and Vicon simultaneously recorded shoulder kinematics. Results: For IMUs, correlation coefficients were high (simple task: >0.968; complex task: >0.84) and RMSEs were low (simple task: <6.72°; complex task: <11.5°). For EMG, a significant effect of weight, height and a weight x height interaction (anterior: p < 0.001; middle: p < 0.03) were observed for RMS EMG activity. Conclusions: These results suggest that wireless EMG and IMUs are valid units that can be used to measure physical demand in workplace assessments.

Validity and Reliability of Wearable Sensors for Joint Angle Estimation: A Systematic Review

Motion capture systems are recognized as the gold standard for joint angle calculation. However, studies using these systems are restricted to laboratory settings for technical reasons, which may lead to findings that are not representative of real-life context. Recently developed commercial and home-made inertial measurement sensors (M/IMU) are potentially good alternatives to the laboratory-based systems, and recent technology improvements required a synthesis of the current evidence. The aim of this systematic review was to determine the criterion validity and reliability of M/IMU for each body joint and for tasks of different levels of complexity. Five different databases were screened (Pubmed, Cinhal, Embase, Ergonomic abstract, and Compendex). Two evaluators performed independent selection, quality assessment (consensus-based standards for the selection of health measurement instruments [COSMIN] and quality appraisal tools), and data extraction. Forty-two studies were included. Reported validity varied according to task complexity (higher validity for simple tasks) and the joint evaluated (better validity for lower limb joints). More studies on reliability are needed to make stronger conclusions, as the number of studies addressing this psychometric property was limited. M/IMU should be considered as a valid tool to assess whole body range of motion, but further studies are needed to standardize technical procedures to obtain more accurate data.

The assessment of instability in the osteoarthritic knee

Patient-reported instability is a common complaint amongst those with knee arthritis.

Much research has examined the assessment of self-reported instability in the knee; however, no definitive quantitative measure of instability has been developed.

This review focuses on the current literature investigating the nature of self-reported instability in the arthritic knee and discusses the possibilities of further investigation.

Cite this article: EFORT Open Rev 2019;4:70-76. DOI: 10.1302/2058-5241.4.170079

Stance and swing phase knee flexion recover at different rates following total knee arthroplasty: An inertial measurement unit study

Total knee arthroplasty (TKA) is the most common joint replacement in the United States. Range of motion (ROM) monitoring includes idealized clinic measures (e.g. goniometry during passive ROM) that may not accurately represent knee function. Accordingly, a novel, portable, inertial measurement unit (IMU) based ROM measurement method was developed, validated, and implemented. Knee flexion was computed via relative motion between two IMUs and validated via optical motion capture (p > 0.05). Prospective analyses of 10 healthy individuals (5M, 50 ± 19 years) and 20 patients undergoing TKA (3 lost to follow up, 10M, 65 ± 6 years) were completed. Controls wore IMUs for 1-week. Patients wore IMUs for 1-week pre-TKA, 6-weeks immediately post-TKA, and 1-week at 1-year post-TKA. Flexion was computed continuously each day (8-12 h). Metrics included daily maximum flexion and flexion during stance/swing phases of gait. Maximum flexion was equal between cohorts at all time points. Contrastingly, patient stance and swing flexion were reduced pre-TKA, yet improved post-TKA. Specifically, patient stance and swing flexion were reduced below control/pre-TKA values during post-TKA week 1. Stance flexion exceeded pre-TKA and equaled control levels after week 2. However, swing flexion only exceeded pre-TKA and equaled control levels at 1-year post-TKA. This novel method improves upon the accuracy/portability of current methods (e.g. goniometry). Interestingly, surgery did not impact maximum ROM, yet improved the ability to flex during gait allowing more efficient and safe ambulation. This is the first study continuously monitoring long-term flexion before/after TKA. The results offer richer information than clinical measures about expected TKA rehabilitation.

Signal Quality Improvement Algorithms for MEMS Gyroscope-Based Human Motion Analysis Systems: A Systematic Review

Motion sensors such as MEMS gyroscopes and accelerometers are characterized by a small size, light weight, high sensitivity, and low cost. They are used in an increasing number of applications. However, they are easily influenced by environmental effects such as temperature change, shock, and vibration. Thus, signal processing is essential for minimizing errors and improving signal quality and system stability. The aim of this work is to investigate and present a systematic review of different signal error reduction algorithms that are used for MEMS gyroscope-based motion analysis systems for human motion analysis or have the potential to be used in this area. A systematic search was performed with the search engines/databases of the ACM Digital Library, IEEE Xplore, PubMed, and Scopus. Sixteen papers that focus on MEMS gyroscope-related signal processing and were published in journals or conference proceedings in the past 10 years were found and fully reviewed. Seventeen algorithms were categorized into four main groups: Kalman-filter-based algorithms, adaptive-based algorithms, simple filter algorithms, and compensation-based algorithms. The algorithms were analyzed and presented along with their characteristics such as advantages, disadvantages, and time limitations. A user guide to the most suitable signal processing algorithms within this area is presented.

Experience does not influence injury-related joint kinematics and kinetics in distance runners

PURPOSE

Increased running experience and more time spent running appears to be advantageous in reducing injury risk, although the reason behind this is unclear. It is plausible that more experience results in better running mechanics leading to less injuries. Running mechanics are often screened during clinical assessments and targeted for correction in gait retraining, particularly those thought to be global indicators of injury or those associated with elevated knee joint loading. Examining the biomechanics of runners who are less-injury prone can improve our understanding of the significance of faulty running mechanics in relation to injury. Our goal was to examine if running experience was correlated to differences in kinematics and kinetics associated with increased knee joint loading and running-related injury risk.

METHODS

One hundred runners with varying experience ran on a pressure-sensing treadmill at a self-selected speed. Trunk and lower extremity kinematics, spatiotemporal measures, and ground reaction forces were collected. Multiple linear regression was used to assess the association between experience and three-dimensional hip kinematics, sagittal plane lower-extremity mechanics, and ground reaction forces while controlling for age and speed.

RESULTS

Increased running experience was not significantly associated with running mechanics. Increased age was significantly associated with reduced peak knee flexion and increased contact time. Running speed influenced several spatiotemporal, kinematic, and kinetic variables.

CONCLUSION

Increased years of running experience does not appear to significantly influence running mechanics. However, age and running speed do influence biomechanical variables associated with injury in distance runners. Thus, there may be factors, other than running mechanics, that contribute to less risk in more experienced runners.

Octopus: A Design Methodology for Motion Capture Wearables

Human motion capture (MoCap) is widely recognised for its usefulness and application in different fields, such as health, sports, and leisure; therefore, its inclusion in current wearables (MoCap-wearables) is increasing, and it may be very useful in a context of intelligent objects interconnected with each other and to the cloud in the Internet of Things (IoT). However, capturing human movement adequately requires addressing difficult-to-satisfy requirements, which means that the applications that are possible with this technology are held back by a series of accessibility barriers, some technological and some regarding usability. To overcome these barriers and generate products with greater wearability that are more efficient and accessible, factors are compiled through a review of publications and market research. The result of this analysis is a design methodology called Octopus, which ranks these factors and schematises them. Octopus provides a tool that can help define design requirements for multidisciplinary teams, generating a common framework and offering a new method of communication between them.

Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion

Motion tracking based on commercial inertial measurements units (IMUs) has been widely studied in the latter years as it is a cost-effective enabling technology for those applications in which motion tracking based on optical technologies is unsuitable. This measurement method has a high impact in human performance assessment and human-robot interaction. IMU motion tracking systems are indeed self-contained and wearable, allowing for long-lasting tracking of the user motion in situated environments. After a survey on IMU-based human tracking, five techniques for motion reconstruction were selected and compared to reconstruct a human arm motion. IMU based estimation was matched against motion tracking based on the Vicon marker-based motion tracking system considered as ground truth. Results show that all but one of the selected models perform similarly (about 35 mm average position estimation error).

Exploring various orientation measurement approaches applied to a serious game system for functional rehabilitation

Serious games have been established as a complementary tool for conventional rehabilitation. This trend proved to be beneficial for both experts and patients since the first are able to assign and monitor virtual reality games for their patients to be executed at home, and the latter are greatly motivated by the challenges of these games rather than the repeatable and boring rehabilitation movements. In a previous work, we proposed a serious game for lower limb rehabilitation of the musculoskeletal system using the Microsoft KinectTM camera and a virtual environment. However, this system suffers from inaccurate kinematic measurement due to various external sources. Therefore, this paper explores various kinematic measurement technics to improve the accuracy of our system. Six real time orientation measurement algorithms were assessed and compared, using multiple types of sensors. The results obtained showed a better performance for our system. In fact, this study reinforced a clearer view on a low cost, real time portable system to be implemented at home.

Joint Inertial Sensor Orientation Drift Reduction for Highly Dynamic Movements

Inertial sensor drift is usually corrected on a single-sensor unit level. When multiple sensor units are used, mutual information from different units can be exploited for drift correction. This study introduces a method for a drift-reduced estimation of three dimensional (3-D) segment orientations and joint angles for motion capture of highly dynamic movements as present in many sports. 3-D acceleration measured on two adjacent segments is mapped to the connecting joint. Drift is estimated and reduced based on the mapped accelerations' vector orientation differences in the global frame. Algorithm validity is assessed on the example of alpine ski racing. Shank, thigh, and trunk inclination as well as knee and hip flexion were compared to a multicamera-based reference system. For specific leg angles and trunk segment inclination mean accuracy and precision were below 3.9° and 6.0°, respectively. The errors were similar to errors reported in other studies for lower dynamic movements. Drift increased axis misalignment and mainly affected joint and segment angles of highly flexed joints such as the knee or hip during a ski turn.

A New Multi-Sensor Fusion Scheme to Improve the Accuracy of Knee Flexion Kinematics for Functional Rehabilitation Movements

Exergames have been proposed as a potential tool to improve the current practice of musculoskeletal rehabilitation. Inertial or optical motion capture sensors are commonly used to track the subject's movements. However, the use of these motion capture tools suffers from the lack of accuracy in estimating joint angles, which could lead to wrong data interpretation. In this study, we proposed a real time quaternion-based fusion scheme, based on the extended Kalman filter, between inertial and visual motion capture sensors, to improve the estimation accuracy of joint angles. The fusion outcome was compared to angles measured using a goniometer. The fusion output shows a better estimation, when compared to inertial measurement units and Kinect outputs. We noted a smaller error (3.96°) compared to the one obtained using inertial sensors (5.04°). The proposed multi-sensor fusion system is therefore accurate enough to be applied, in future works, to our serious game for musculoskeletal rehabilitation.

Human Pose Estimation from Video and IMUs

In this work, we present an approach to fuse video with sparse orientation data obtained from inertial sensors to improve and stabilize full-body human motion capture. Even though video data is a strong cue for motion analysis, tracking artifacts occur frequently due to ambiguities in the images, rapid motions, occlusions or noise. As a complementary data source, inertial sensors allow for accurate estimation of limb orientations even under fast motions. However, accurate position information cannot be obtained in continuous operation. Therefore, we propose a hybrid tracker that combines video with a small number of inertial units to compensate for the drawbacks of each sensor type: on the one hand, we obtain drift-free and accurate position information from video data and, on the other hand, we obtain accurate limb orientations and good performance under fast motions from inertial sensors. In several experiments we demonstrate the increased performance and stability of our human motion tracker.

Human Joint Angle Estimation with Inertial Sensors and Validation with A Robot Arm

Traditionally, human movement has been captured primarily by motion capture systems. These systems are costly, require fixed cameras in a controlled environment, and suffer from occlusion. Recently, the availability of low-cost wearable inertial sensors containing accelerometers, gyroscopes, and magnetometers have provided an alternative means to overcome the limitations of motion capture systems. Wearable inertial sensors can be used anywhere, cannot be occluded, and are low cost. Several groups have described algorithms for tracking human joint angles. We previously described a novel approach based on a kinematic arm model and the Unscented Kalman Filter (UKF). Our proposed method used a minimal sensor configuration with one sensor on each segment. This paper reports significant improvements in both the algorithm and the assessment. The new model incorporates gyroscope and accelerometer random drift models, imposes physical constraints on the range of motion for each joint, and uses zero-velocity updates to mitigate the effect of sensor drift. A high-precision industrial robot arm precisely quantifies the performance of the tracker during slow, normal, and fast movements over continuous 15-min recording durations. The agreement between the estimated angles from our algorithm and the high-precision robot arm reference was excellent. On average, the tracker attained an RMS angle error of about 3(°) for all six angles. The UKF performed slightly better than the more common Extended Kalman Filter.

A basic study on quantitative evaluation of 3-dimensional foot contact with an inertial sensor for FES foot drop correction

In these days, FES is used to control ankle dorsiflexion of hemiplegic gait. Since not only dorsiflexion but also 3-dimensional foot contact isimportant for gait stability in hemiplegic gait, evaluation and control system of 3-dimensional foot contact with FES is needed to correct foot movement. In this study, the timing of initial contact and the timing when foot movement became stationary in the sagittal plane were detected, and the inclination angles in the sagittal and the frontal planes at these timings were used for evaluation. Using the inclination angles, 10 m walking of a hemiplegic subject under the 4 different gait conditions were quantitatively evaluated. The gait conditions were without FES, stimulation to the tibialis anterior, stimulation to the common peroneal nerve, and stimulation to both the tibialis anterior and the common peroneal nerve. Result of evaluation with the inclination angles showed that stimulation to the tibialis anterior could control foot contact appropriately in the sagittal plane, and stimulation to the common peroneal nerve was better to control foot inclination angle in the frontal plane. Inclination angle at the beginning of the stance phase indicated that FES system which used in clinical site commonly is not appropriate to control 3-dimensional foot contact. It was shown that inclination angle at the beginning of the stance phase was useful to evaluate 3-dimensional foot movements for FES foot drop correction.

Drift removal for improving the accuracy of gait parameters using wearable sensor systems

Accumulated signal noise will cause the integrated values to drift from the true value when measuring orientation angles of wearable sensors. This work proposes a novel method to reduce the effect of this drift to accurately measure human gait using wearable sensors. Firstly, an infinite impulse response (IIR) digital 4th order Butterworth filter was implemented to remove the noise from the raw gyro sensor data. Secondly, the mode value of the static state gyro sensor data was subtracted from the measured data to remove offset values. Thirdly, a robust double derivative and integration method was introduced to remove any remaining drift error from the data. Lastly, sensor attachment errors were minimized by establishing the gravitational acceleration vector from the acceleration data at standing upright and sitting posture. These improvements proposed allowed for removing the drift effect, and showed an average of 2.1°, 33.3°, 15.6° difference for the hip knee and ankle joint flexion/extension angle, when compared to without implementation. Kinematic and spatio-temporal gait parameters were also calculated from the heel-contact and toe-off timing of the foot. The data provided in this work showed potential of using wearable sensors in clinical evaluation of patients with gait-related diseases.

Kinematics based sensory fusion for wearable motion assessment in human walking

Measuring the kinematic parameters in unconstrained human motion is becoming crucial for providing feedback information in wearable robotics and sports monitoring. This paper presents a novel sensory fusion algorithm for assessing the orientations of human body segments in long-term human walking based on signals from wearable sensors. The basic idea of the proposed algorithm is to constantly fuse the measured segment's angular velocity and linear acceleration via known kinematic relations between segments. The wearable sensory system incorporates seven inertial measurement units attached to the human body segments and two instrumented shoe insoles. The proposed system was experimentally validated in a long-term walking on a treadmill and on a polygon with stairs simulating different activities in everyday life. The outputs were compared to the reference parameters measured by a stationary optical system. Results show accurate joint angle measurements (error median below 5°) in all evaluated walking conditions with no expressed drift over time.

Kinematic parameters to evaluate functional performance of sit-to-stand and stand-to-sit transitions using motion sensor devices: a systematic review

Clinicians commonly use questionnaires and tests based on daily life activities to evaluate physical function. However, the outcomes are usually more qualitative than quantitative and subtle differences are not detectable. In this review, we aim to assess the role of body motion sensors in physical performance evaluation, especially for the sit-to-stand and stand-to-sit transitions. In total, 53 full papers and conference abstracts on related topics were included and 16 different parameters related to transition performance were identified as potentially meaningful to explain certain disabilities and impairments. Transition duration is the most used to evaluate chair-related tests in real clinical settings. High-fall-risk fallers and frail subjects presented longer and more variable transition duration. Other kinematic parameters have also been highlighted in the literature as potential means to detect age-related impairments. In particular, vertical linear velocity and trunk tilt range were able to differentiate between different frailty levels. Frequency domain measures such as spectral edge frequency were also higher for elderly fallers. Lastly, approximate entropy values were larger for subjects with Parkinson's disease and were significantly reduced after treatment. This information could help clinicians in their evaluations as well as in prescribing a physical fitness program to correct a specific deficit.

The use of accelerometers and gyroscopes to estimate hip and knee angles on gait analysis

In this paper the performance of a sensor system, which has been developed to estimate hip and knee angles and the beginning of the gait phase, have been investigated. The sensor system consists of accelerometers and gyroscopes. A new algorithm was developed in order to avoid the error accumulation due to the gyroscopes drift and vibrations due to the ground contact at the beginning of the stance phase. The proposed algorithm have been tested and compared to some existing algorithms on over-ground walking trials with a commercial device for assisted gait. The results have shown the good accuracy of the angles estimation, also in high angle rate movement.

Quantified self and human movement: a review on the clinical impact of wearable sensing and feedback for gait analysis and intervention

The proliferation of miniaturized electronics has fueled a shift toward wearable sensors and feedback devices for the mass population. Quantified self and other similar movements involving wearable systems have gained recent interest. However, it is unclear what the clinical impact of these enabling technologies is on human gait. The purpose of this review is to assess clinical applications of wearable sensing and feedback for human gait and to identify areas of future research. Four electronic databases were searched to find articles employing wearable sensing or feedback for movements of the foot, ankle, shank, thigh, hip, pelvis, and trunk during gait. We retrieved 76 articles that met the inclusion criteria and identified four common clinical applications: (1) identifying movement disorders, (2) assessing surgical outcomes, (3) improving walking stability, and (4) reducing joint loading. Characteristics of knee and trunk motion were the most frequent gait parameters for both wearable sensing and wearable feedback. Most articles performed testing on healthy subjects, and the most prevalent patient populations were osteoarthritis, vestibular loss, Parkinson's disease, and post-stroke hemiplegia. The most widely used wearable sensors were inertial measurement units (accelerometer and gyroscope packaged together) and goniometers. Haptic (touch) and auditory were the most common feedback sensations. This review highlights the current state of the literature and demonstrates substantial potential clinical benefits of wearable sensing and feedback. Future research should focus on wearable sensing and feedback in patient populations, in natural human environments outside the laboratory such as at home or work, and on continuous, long-term monitoring and intervention.

A portable system with sample rate of 250 Hz for characterization of knee and hip angles in the sagittal plane during gait

Background

Gait analysis and research have been developed to obtain characteristics of movement patterns of people while walking. However, traditional measuring systems present different drawbacks that reduce their use and application. Among those drawbacks one can find: high price, low sampling frequency and limiting number of steps to be analyzed. Traditional measuring gait systems carry out their measurement at frequencies oscillating between 60 to 100 Hz. It can be argued about the need of higher sampling rates for gait measurements. However small displacements of the knee or hip for example, cannot be seen with low frequencies required a more detailed sampling and higher frequency sampling. Bearing this in mind, in this paper is presented a 250 Hz system based on accelerometers for gait measurement, and the particularities of knee and hip angles during gait are highlighted.

Methods

The system was designed with a PCI data acquisition card instrumented with an FPGA to achieve a rate sample of 250 Hz. The accelerometers were placed in thighs and legs to calculate the joint angles of hip and knee in the sagittal plane. The angles were estimated using the acceleration polygon method without integrating the acceleration and without filters.

Results

The gait of thirty healthy people of Mexican phenotype was analyzed over a flat floor free of obstacles. The results showed the gait phases and particularities associated with the walking style and people's laterality; the movement patterns were similar in the thirty persons. Based on the results, the particularities as the maximum amplitude in the angles and the shape in the movement patterns were related to the anthropometry and people phenotype.

Conclusions

The sampling frequency was essential to record 340 samples in single gait cycle and so registering the gait cycle with its particularities. In this work were recorded an average of 8 to 10 gait cycles, and the results showed variation regarding works carried out in biomechanics laboratories; this variation was related to the method and reference frame used to obtain the joint angles and the accuracy of measurement system.