Estimation of the Knee Adduction Moment and Joint Contact Force during Daily Living Activities Using Inertial Motion Capture.

Knee osteoarthritis is a major cause of pain and disability in the elderly population with many daily living activities being difficult to perform as a result of this disease. The present study aimed to estimate the knee adduction moment and tibiofemoral joint contact force during daily living activities using a musculoskeletal model with inertial motion capture derived kinematics in an elderly population. Eight elderly participants were instrumented with 17 inertial measurement units, as well as 53 opto-reflective markers affixed to anatomical landmarks. Participants performed stair ascent, stair descent, and sit-to-stand movements while both motion capture methods were synchronously recorded. A musculoskeletal model containing 39 degrees-of-freedom was used to estimate the knee adduction moment and tibiofemoral joint contact force. Strong to excellent Pearson correlation coefficients were found for the IMC-derived kinematics across the daily living tasks with root mean square errors (RMSE) between 3° and 7°. Furthermore, moderate to strong Pearson correlation coefficients were found in the knee adduction moment and tibiofemoral joint contact forces with RMSE between 0.006⁻0.014 body weight × body height and 0.4 to 1 body weights, respectively. These findings demonstrate that inertial motion capture may be used to estimate knee adduction moments and tibiofemoral contact forces with comparable accuracy to optical motion capture.

Musculoskeletal model-based inverse dynamic analysis under ambulatory conditions using inertial motion capture.

Inverse dynamic analysis using musculoskeletal modeling is a powerful tool, which is utilized in a range of applications to estimate forces in ligaments, muscles, and joints, non-invasively. To date, the conventional input used in this analysis is derived from optical motion capture (OMC) and force plate (FP) systems, which restrict the application of musculoskeletal models to gait laboratories. To address this problem, we propose the use of inertial motion capture to perform musculoskeletal model-based inverse dynamics by utilizing a universally applicable ground reaction force and moment (GRF&M) prediction method. Validation against a conventional laboratory-based method showed excellent Pearson correlations for sagittal plane joint angles of ankle, knee, and hip (ρ=0.95, 0.99, and 0.99, respectively) and root-mean-squared-differences (RMSD) of 4.1 ±â€¯1.3°, 4.4 ±â€¯2.0°, and 5.7 ±â€¯2.1°, respectively. The GRF&M predicted using IMC input were found to have excellent correlations for three components (vertical: ρ=0.97, RMSD = 9.3 ±â€¯3.0 %BW, anteroposterior: ρ=0.91, RMSD = 5.5 ±â€¯1.2 %BW, sagittal: ρ=0.91, RMSD = 1.6 ±â€¯0.6 %BW*BH), and strong correlations for mediolateral (ρ=0.80, RMSD = 2.1 ±â€¯0.6 %BW) and transverse (ρ=0.82, RMSD = 0.2 ±â€¯0.1 %BW*BH). The proposed IMC-based method removes the complexity and space restrictions of OMC and FP systems and could enable applications of musculoskeletal models in either monitoring patients during their daily lives or in wider clinical practice.

Validation of wearable visual feedback for retraining foot progression angle using inertial sensors and an augmented reality headset.

BACKGROUND: Gait retraining interventions using real-time biofeedback have been proposed to alter the loading across the knee joint in patients with knee osteoarthritis. Despite the demonstrated benefits of these conservative treatments, their clinical adoption is currently obstructed by the high complexity, spatial demands, and cost of optical motion capture systems. In this study we propose and evaluate a wearable visual feedback system for gait retraining of the foot progression angle (FPA). METHODS: The primary components of the system are inertial measurement units, which track the human movement without spatial limitations, and an augmented reality headset used to project the visual feedback in the visual field. The adapted gait protocol contained five different target angles ranging from 15 degrees toe-out to 5 degrees toe-in. Eleven healthy participants walked on an instrumented treadmill, and the protocol was performed using both an established laboratory visual feedback driven by optical motion capture, and the proposed wearable system. RESULTS AND CONCLUSIONS: The wearable system tracked FPA with an accuracy of 2.4 degrees RMS and ICC=0.94 across all target angles and subjects, when compared to an optical motion capture reference. In addition, the effectiveness of the biofeedback, reflected by the number of steps with FPA value ±2 degrees from the target, was found to be around 50% in both wearable and laboratory approaches. These findings demonstrate that retraining of the FPA using wearable inertial sensing and visual feedback is feasible with effectiveness matching closely an established laboratory method. The proposed wearable setup may reduce the complexity of gait retraining applications and facilitate their transfer to routine clinical practice.

Analysis of Balance during Functional Walking in Stroke Survivors.

BACKGROUND: An important objective of rehabilitation care is to regain adequate balance function to safely ambulate in community. However, in rehabilitation practice, it remains unclear if a stroke survivor functionally recovers by restitution or by learning to compensate for the lack of restoration of body function. Aim of this study is to propose and evaluate methods for the objective evaluation of balance during functional walking in stroke survivors. METHODS: Stroke survivors performed twice a Timed "Up & Go" (TUG) test. Ground reaction forces and position changes of both feet were measured using instrumented shoes and used to estimate the position of the center of mass (CoM). Balance control and efficiency metrics were defined to evaluate functional walking under variable conditions. Metrics were corrected based on the instantaneous velocity direction of CoM. Intra- and inter-participant variations for different phases of the TUG test were examined. Metrics were related to the Berg balance scale (BBS). RESULTS: Participants with higher BBS scores show a more efficient walking pattern. Their walking velocity and walking direction is less variable and they are more frequently unstable when walking in a straight line or when turning. Furthermore, the less affected participants are able to move their CoM more towards their affected side. DISCUSSION: We developed and demonstrated a method to assess walking balance of stroke survivors. System design and evaluation methods allow balance evaluation during functional walking in daily life. Some presented metrics show correlations with BBS scores. Clear inter- and intra-patient variations in metric values are present that cannot be explained by BBS scores, which supports the additional value of the presented system. Presented methods may be used for objective evaluation of restitution and compensation of walking balance and have a potential application in individual evidence-based therapy.

Identification of Object Dynamics Using Hand Worn Motion and Force Sensors.

Emerging microelectromechanical system (MEMS)-based sensors become much more applicable for on-body measurement purposes lately. Especially, the development of a finger tip-sized tri-axial force sensor gives the opportunity to measure interaction forces between the human hand and environmental objects. We have developed a new prototype device that allows simultaneous 3D force and movement measurements at the finger and thumb tips. The combination of interaction forces and movements makes it possible to identify the dynamical characteristics of the object being handled by the hand. With this device attached to the hand, a subject manipulated mass and spring objects under varying conditions. We were able to identify and estimate the weight of two physical mass objects (0.44 kg: 29 . 3 % ± 18 . 9 % and 0.28 kg: 19 . 7 % ± 10 . 6 % ) and the spring constant of a physical spring object ( 16 . 3 % ± 12 . 6 % ). The system is a first attempt to quantify the interactions of the hand with the environment and has many potential applications in rehabilitation, ergonomics and sports.

Estimation of Ground Reaction Forces and Moments During Gait Using Only Inertial Motion Capture.

Ground reaction forces and moments (GRF&M) are important measures used as input in biomechanical analysis to estimate joint kinetics, which often are used to infer information for many musculoskeletal diseases. Their assessment is conventionally achieved using laboratory-based equipment that cannot be applied in daily life monitoring. In this study, we propose a method to predict GRF&M during walking, using exclusively kinematic information from fully-ambulatory inertial motion capture (IMC). From the equations of motion, we derive the total external forces and moments. Then, we solve the indeterminacy problem during double stance using a distribution algorithm based on a smooth transition assumption. The agreement between the IMC-predicted and reference GRF&M was categorized over normal walking speed as excellent for the vertical (ρ = 0.992, rRMSE = 5.3%), anterior (ρ = 0.965, rRMSE = 9.4%) and sagittal (ρ = 0.933, rRMSE = 12.4%) GRF&M components and as strong for the lateral (ρ = 0.862, rRMSE = 13.1%), frontal (ρ = 0.710, rRMSE = 29.6%), and transverse GRF&M (ρ = 0.826, rRMSE = 18.2%). Sensitivity analysis was performed on the effect of the cut-off frequency used in the filtering of the input kinematics, as well as the threshold velocities for the gait event detection algorithm. This study was the first to use only inertial motion capture to estimate 3D GRF&M during gait, providing comparable accuracy with optical motion capture prediction. This approach enables applications that require estimation of the kinetics during walking outside the gait laboratory.

Hand Pose Estimation by Fusion of Inertial and Magnetic Sensing Aided by a Permanent Magnet.

Tracking human body motions using inertial sensors has become a well-accepted method in ambulatory applications since the subject is not confined to a lab-bounded volume. However, a major drawback is the inability to estimate relative body positions over time because inertial sensor information only allows position tracking through strapdown integration, but does not provide any information about relative positions. In addition, strapdown integration inherently results in drift of the estimated position over time. We propose a novel method in which a permanent magnet combined with 3-D magnetometers and 3-D inertial sensors are used to estimate the global trunk orientation and relative pose of the hand with respect to the trunk. An Extended Kalman Filter is presented to fuse estimates obtained from inertial sensors with magnetic updates such that the position and orientation between the human hand and trunk as well as the global trunk orientation can be estimated robustly. This has been demonstrated in multiple experiments in which various hand tasks were performed. The most complex task in which simultaneous movements of both trunk and hand were performed resulted in an average rms position difference with an optical reference system of 19.7±2.2 mm whereas the relative trunk-hand and global trunk orientation error was 2.3±0.9 and 8.6±8.7 deg respectively.

Use of inertial sensors for ambulatory assessment of center-of-mass displacements during walking.

Current methods for center-of-mass (CoM) estimation are restricted to gait laboratories. The aim of this study was to estimate CoM displacement under ambulatory conditions with inertial sensors. A sacral inertial sensor (SIS method) was used to estimate the CoM displacement by double integration of the acceleration. Overestimation of the displacement caused by pelvic rotations was compensated (CSIS method). The CoM displacement estimations using the (C)SIS method were compared to the conventional methods of the segmental analysis (SA) method and the sacral marker (SM) method by the intraclass correlations and the root-mean-square (RMS) differences between the CoM curves. Accurate ambulatory measurement of the CoM displacement using inertial sensors was possible. Estimations of the sacrum position using the SIS method and the SM method were similar with mean (SD) RMS differences of 3.23 (0.87), 2.96 (0.42), and 3.22 (0.78) mm for, respectively, the x-, y- and z-directions. The CoM estimation of the SIS method has RMS differences of 5.67 (1.20), 7.16 (3.28), and 3.49 (1.29) mm compared the SA method. The CSIS method shows a clear improvement in these estimations of the CoM with RMS differences of 5.52 (1.29), 4.44 (1.89), and 3.17 (1.41) mm and is generally applicable for healthy subjects.

A force plate based method for the calibration of force/torque sensors.

This study describes a novel calibration method for six-degrees-of-freedom force/torque sensors (FTsensors) using a pre-calibrated force plate (FP) as a reference measuring device. In this calibration method, the FTsensor is rigidly connected to a FP and force/torque data are synchronously recorded while a dynamic functional loading procedure is applied by the researcher. Based on these data an accurate calibration matrix for the FTsensor can easily be obtained via least-squares optimization. Using this calibration method, this study further investigated what loading methods are appropriate for the calibration of FTsensors intended for ambulatory measurement of ground reaction forces (GRFs). Seven different loading methods were compared (e.g., walking, pushing while standing on the FTsensor). Calibration matrices were calculated based on the raw data from the seven loading methods individually and all loading methods combined. Performance of these calibration matrices was subsequently compared in an in situ trial. During the in situ trial, five common work tasks (e.g., walking, manual lifting, pushing) were performed by an experimenter, while standing on the FP wearing a "ForceShoe" with two calibrated FTsensors attached to its sole. Root-mean-square differences (RMSDs) between the FTsensor and FP outcomes were calculated over all tasks. Using the calibration matrices based on all loading methods combined resulted in small RMSDs (GRF: <8 N, center of pressure: <2 mm). Using the calibration matrices based on "pushing against manual resistance" resulted in similar RMSDs, proving it to be the best single loading method.

The knee adduction moment measured with an instrumented force shoe in patients with knee osteoarthritis.

The external knee adduction moment (KAdM) during gait is an important parameter in patients with knee osteoarthritis (OA). KAdM measurement is currently restricted to instruments only available in gait laboratories. However, ambulatory movement analysis technology, including instrumented force shoes (IFS) and inertial and magnetic measurement systems (IMMS), can measure kinetics and kinematics of human gait free of laboratory restrictions. The objective of this study was a quantitative validation of the accuracy of the KAdM in patients with knee OA, when estimated with an ambulatory-based method (AmbBM) versus a laboratory-based method (LabBM). AmbBM is employing the IFS and a linked-segment model, while LabBM is based on a force plate and optoelectronic marker system. Effects of ground reaction force (GRF), centre of pressure (CoP), and knee joint position measurement are evaluated separately. Twenty patients with knee OA were measured. The GRFs showed differences up to 0.22 N/kg, the CoPs showed differences up to 4 mm, and the medio-lateral and vertical knee position showed differences to 9 mm, between AmbBM and LabBM. The GRF caused an under-estimation in KAdM in early stance. However, this effect was counteracted by differences in CoP and joint position, resulting in a net 5% over-estimation. In midstance and late stance the accuracy of the KAdM was mainly limited by use of the linked-segment model for joint position estimation, resulting in an under-estimation (midstance 6% and late stance 22%). Further improvements are needed in the estimation of joint position from segment orientation.

Ambulatory human motion tracking by fusion of inertial and magnetic sensing with adaptive actuation.

Over the last years, inertial sensing has proven to be a suitable ambulatory alternative to traditional human motion tracking based on optical position measurement systems, which are generally restricted to a laboratory environment. Besides many advantages, a major drawback is the inherent drift caused by integration of acceleration and angular velocity to obtain position and orientation. In addition, inertial sensing cannot be used to estimate relative positions and orientations of sensors with respect to each other. In order to overcome these drawbacks, this study presents an Extended Kalman Filter for fusion of inertial and magnetic sensing that is used to estimate relative positions and orientations. In between magnetic updates, change of position and orientation are estimated using inertial sensors. The system decides to perform a magnetic update only if the estimated uncertainty associated with the relative position and orientation exceeds a predefined threshold. The filter is able to provide a stable and accurate estimation of relative position and orientation for several types of movements, as indicated by the average rms error being 0.033 m for the position and 3.6 degrees for the orientation.

Sensing power transfer between the human body and the environment.

The power transferred between the human body and the environment at any time and the work performed are important quantities to be estimated when evaluating and optimizing the physical interaction between the human body and the environment in sports, physical labor, and rehabilitation. It is the objective of the current paper to present a concept for estimating power transfer between the human body and the environment during free motions and using sensors at the interface, not requiring measurement systems in the environment, and to experimentally demonstrate this principle. Mass and spring loads were moved by hand over a fixed height difference via varying free movement trajectories. Kinematic and kinetic quantities were measured in the handle between the hand and the load. 3-D force and moments were measured using a 6 DOF force/moment sensor module, 3-D movement was measured using 3-D accelerometers and angular velocity sensors. The orientation was estimated from the angular velocity, using the initial orientation as a begin condition. The accelerometer signals were expressed in global coordinates using this orientation information. Velocity was estimated by integrating acceleration in global coordinates, obtained by adding gravitational acceleration to the accelerometer signals. Zero start and end velocities were used as begin and end conditions. Power was calculated as the sum of the inner products of velocity and force and of angular velocity and moment, and work was estimated by integrating power over time. The estimated performed work was compared to the potential energy difference corresponding to the change in height of the loads and appeared to be accurate within 4% for varying movements with net displacements and varying loads (mass and spring). The principle of estimating power transfer demonstrated in this paper can be used in future interfaces between the human body and the environment instrumented with body-mounted miniature 3-D force and acceleration sensors.

Ambulatory estimation of center of mass displacement during walking.

The center of mass (CoM) and the center of pressure (CoP) are two variables that are crucial in assessing energy expenditure and stability of human walking. The purpose of this study is to estimate the CoM displacement continuously using an ambulatory measurement system. The measurement system consists of instrumented shoes with 6 DOF force/moment sensors beneath the heels and the forefeet. Moreover, two inertial sensors are rigidly attached to the force/moment sensors for the estimation of position and orientation. The estimation of CoM displacement is achieved by fusing low-pass filtered CoP data with high-pass filtered double integrated CoM acceleration, both estimated using the instrumented shoes. Optimal cutoff frequencies for the low-pass and high-pass filters appeared to be 0.2 Hz for the horizontal direction and 0.5 Hz for the vertical direction. The CoM estimation using this ambulatory measurement system was compared to CoM estimation using an optical reference system based on the segmental kinematics method. The rms difference of each component of the CoM displacement averaged over a hundred trials obtained from seven stroke patients was ( 0.020 +/-0.007 ) m (mean +/- standard deviation) for the forward x-direction, ( 0.013 +/-0.005) m for the lateral y-direction, and ( 0.007 +/-0.001) m for the upward z-direction. Based on the results presented in this study, it is concluded that the instrumented shoe concept allows accurate and continuous estimation of CoM displacement under ambulatory conditions.

Ambulatory assessment of ankle and foot dynamics.

Ground reaction force (GRF) measurement is important in the analysis of human body movements. The main drawback of the existing measurement systems is the restriction to a laboratory environment. This paper proposes an ambulatory system for assessing the dynamics of ankle and foot, which integrates the measurement of the GRF with the measurement of human body movement. The GRF and the center of pressure (CoP) are measured using two six-degrees-of-freedom force sensors mounted beneath the shoe. The movement of foot and lower leg is measured using three miniature inertial sensors, two rigidly attached to the shoe and one on the lower leg. The proposed system is validated using a force plate and an optical position measurement system as a reference. The results show good correspondence between both measurement systems, except for the ankle power estimation. The root mean square (RMS) difference of the magnitude of the GRF over 10 evaluated trials was (0.012 +/- 0.001) N/N (mean +/- standard deviation), being (1.1 +/- 0.1)% of the maximal GRF magnitude. It should be noted that the forces, moments, and powers are normalized with respect to body weight. The CoP estimation using both methods shows good correspondence, as indicated by the RMS difference of (5.1 +/- 0.7) mm, corresponding to (1.7 +/- 0.3)% of the length of the shoe. The RMS difference between the magnitudes of the heel position estimates was calculated as (18 +/- 6) mm, being (1.4 +/- 0.5)% of the maximal magnitude. The ankle moment RMS difference was (0.004 +/- 0.001) Nm/N, being (2.3 +/- 0.5)% of the maximal magnitude. Finally, the RMS difference of the estimated power at the ankle was (0.02 +/- 0.005) W/N, being (14 +/- 5)% of the maximal power. This power difference is caused by an inaccurate estimation of the angular velocities using the optical reference measurement system, which is due to considering the foot as a single segment. The ambulatory system considers separate heel and forefoot segments, thus allowing an additional foot moment and power to be estimated. Based on the results of this research, it is concluded that the combination of the instrumented shoe and inertial sensing is a promising tool for the assessment of the dynamics of foot and ankle in an ambulatory setting.