Quantification of Triple Single-Leg Hop Test Temporospatial Parameters: A Validated Method using Body-Worn Sensors for Functional Evaluation after Knee Injury

The Influence of Ankle Mobility and Foot Stability on Jumping Ability and Landing Mechanics: A Cross-Sectional Study

Practicing physical activities or sports that involve frequent jumping and landing can strain the muscles and joints of the lower limbs, especially in those who do not have adequate physical preparation. The objective of this study was to (a) determine the correlation between ankle range of motion (ROM) and landing stability following jumps; (b) assess the association between the jump height in a counter-movement jump (CMJ) test and ankle ROM; and (c) examine the connection between stabilometry during specific jumps movements present in many sports and in ankle stabilization. Sixty-two healthy amateur volleyball players participated in the study (age: thirty-seven females and twenty-five males; age (years): 16.5 ± 4.25; height (cm): 166 ± 11.4; weight (Kg): 61.6 ± 13.7). Participants were recruited for the study in collaboration with student sports associations. The evaluations encompassed the measurement of ankle joint mobility for both lower limbs using an inertial sensor, a static baropodometric and stabilometric analysis using a pressure platform, and the CMJ test using the Microgate system. After the assessments, participants performed a "specific jump landing task". Significant correlations were found between foot range of motion (ROM) and counter-movement jump (CMJ) performance. Specifically, the ROM of the right foot had a strong correlation with the CMJ (r = 0.81, p < 0.001), while the left foot ROM showed a moderate correlation (r = 0.46, p < 0.001). The specific jump task revealed substantial changes in stabilometry parameters, particularly during forward hops compared to lateral jumps. Dorsiflexion ROM significantly impacts jumping ability. Evaluating landing patterns and stabilometry during targeted activities can help optimize training, improve dynamic balance, and reduce ankle injury risk.

Reliability and Validity of Temporal Parameters during the Side Hop Test in Patients after Anterior Cruciate Ligament Reconstruction

Background: The side hop test (SHT) measures the number of jumps performed over 30 s. Although this measure has demonstrated its value in clinical practice, the temporal parameters of the SHT allow for a deeper analysis of the execution strategy. The aim of this study is to assess the reliability and construct validity of contact time parameters during the SHT recorded by a video analysis system in anterior cruciate ligament reconstructed (ACLR) patients. Methods: We investigated the reliability (intra-rater, standard error of measurement (SEM), and minimum detectable change (MDC)), discriminant validity (operated (OP) versus non-operated (NOP) side), and convergent validity (relationship with strength and psychological readiness) of SHT contact time parameters, number of valid hops and limb symmetry index (LSI) in 38 ACLR patients. Contact time parameters are presented as mean, standard deviation (SD), and coefficient of variation (CV) of contact time. Results: Intra-tester reliability was good to excellent for all contact time parameters. For discriminant validity, the mean and SD contact times of the OP leg were significantly longer than those of the NOP leg, although the difference was smaller than the SEM and MDC values. The number of valid jumps and CV contact time parameters were not significantly different. Isokinetic quadriceps strength (60°/s) was strongly correlated with mean contact time for both legs. However, psychological readiness was not correlated with any of the contact time parameters. Conclusions: Temporal parameters of the SHT measured on video analysis are valid and reliable parameters to assess the performance strategy of the SHT. The results should be interpreted with caution regarding the SEM and MDC values. Further studies are needed to measure criterion validity, inter-rater reliability, and responsiveness.

Reliability of Spatiotemporal Characteristics During Single-Legged Hop and Bilateral Drop Jump Tasks Using an Instrumented Pressure Walkway

Background

Single-legged hop tests have been widely used to assess performance-based outcomes after anterior cruciate ligament (ACL) reconstruction. Traditional single, triple, or 6-meter (6m) timed hop tests only measure distance or time as the principal variables, neglecting other variables, such as individual hop distances within a series of hops, flight time, and stance time. The development of portable instrumented pressure walkways has made it possible to collect parameters such as hop velocity, flight time, stance time, distance, and pressure outside of a laboratory setting. However, the reliability of instrumented pressure walkways in measuring spatial and temporal variables during single-legged hop tests is unknown. This study aimed to determine if the Zeno walkway can reliably measure spatiotemporal (ST) characteristics of hop tests.

Study Design

Cross-Sectional Study.

Methods

Individuals (n=38) in this cross-sectional study performed single, triple, and 6m hop tests on a pressure-sensitive Zeno walkway. Twenty-one participants completed follow-up testing between one and 14 days later. Intraclass correlation coefficients (ICC(3,k)) were used to assess test-retest reliability of ST variables. The accuracy of vertical jump height and 6m hop timing were also measured.

Results

All ST variables demonstrated excellent test-retest reliability (ICC > 0.86) with small minimal detectable change (MDC) values during single-legged hop tests. Six-meter hop time and jump height during a bilateral drop jump were also accurately measured by the walkway.

Conclusion

An instrumented pressure walkway is a novel tool to reliably assess non-traditional parameters of clinically relevant hop and jump tests such as flight time, stance time, and jump height after lower extremity injury, surgery, and rehabilitation.

Level of Evidence

3b.

Estimation of lower back muscle force in a lifting task using wearable IMUs

Low back pain is commonly reported in occupational settings due to factors such as heavy lifting and poor ergonomic practices, often resulting in significant healthcare expenses and lowered productivity. Assessment tools for human motion and ergonomic risk at the workplace are still limited. Therefore, this study aimed to assess lower back muscle and joint reaction forces in laboratory conditions using wearable inertial measurement units (IMUs) during weight lifting, a frequently high-risk workplace task. Ten able-bodied participants were instructed to lift a 28 lbs. box while surface electromyography sensors, IMUs, and a camera-based motion capture system recorded their muscle activity and body motion. The data recorded by IMUs and motion capture system were used to estimate lower back muscle and joint reaction forces via musculoskeletal modeling. Lower back muscle patterns matched well with electromyography recordings. The normalized mean absolute differences between muscle forces estimated based on measurements of IMUs and cameras were less than 25 %, and the statistical parametric mapping results indicated no significant difference between the forces estimated by both systems. However, abrupt changes in motion, such as lifting initiation, led to significant differences (p < 0.05) between the muscle forces. Furthermore, the maximum L5-S1 joint reaction force estimated using IMU data was significantly lower (p < 0.05) than those estimated by cameras during weight lifting and lowering. The study showed how kinematic errors from IMUs propagated through the musculoskeletal model and affected the estimations of muscle forces and joint reaction forces. Our findings showed the potential of IMUs for in-field ergonomic risk evaluations.

Effect of test duration and sensor location on the reliability of standing balance parameters derived using body-mounted accelerometers

BACKGROUND

Balance parameters derived from wearable sensor measurements during postural sway have been shown to be sensitive to experimental variables such as test duration, sensor number, and sensor location that influence the magnitude and frequency-related properties of measured center-of-mass (COM) and center-of-pressure (COP) excursions. In this study, we investigated the effects of test duration, the number of sensors, and sensor location on the reliability of standing balance parameters derived using body-mounted accelerometers.

METHODS

Twelve volunteers without any prior history of balance disorders were enrolled in the study. They were asked to perform two 2-min quiet standing tests with two different testing conditions (eyes open and eyes closed). Five inertial measurement units (IMUs) were employed to capture postural sway data from each participant. IMUs were attached to the participants' right legs, the second sacral vertebra, sternum, and the left mastoid processes. Balance parameters of interest were calculated for the single head, sternum, and sacrum accelerometers, as well as, a three-sensor combination (leg, sacrum, and sternum). Accelerometer data were used to estimate COP-based and COM-based balance parameters during quiet standing. To examine the effect of test duration and sensor location, each 120-s recording from different sensor locations was segmented into 20-, 30-, 40-, 50-, 60-, 70-, 80-, 90-, 100-, and 110-s intervals. For each of these time intervals, time- and frequency-domain balance parameters were calculated for all sensor locations.

RESULTS

Most COM-based and COP-based balance parameters could be derived reliably for clinical applications (Intraclass-Correlation Coefficient, ICC ≥ 0.90) with a minimum test duration of 70 and 110 s, respectively. The exceptions were COP-based parameters obtained using a sacrum-mounted sensor, especially in the eyes-closed condition, which could not be reliably used for clinical applications even with a 120-s test duration.

CONCLUSIONS

Most standing balance parameters can be reliably measured using a single head- or sternum-mounted sensor within a 120-s test duration. For other sensor locations, the minimum test duration may be longer and may depend on the specific test conditions.

Estimation of human spine orientation with inertial measurement units (IMU) at low sampling rate: How low can we go?

Studying people in their daily life is important for understanding conditions with multi-faceted aetiology such as chronic low back pain. Inertial measurement units can be used to reconstruct the posture and motion of the body outside of laboratories to enable this research. The battery life of these sensors strongly affects the usability of the system, since recharging them frequently is inconvenient and can lead to additional errors. A major determinant of the battery life for these sensors is sampling rate, but the relationship between sampling rate and accuracy in motion reconstruction is not well documented. We measured the spine of 12 participants using inertial measurement units across a variety of tasks such as sitting, standing, walking, and jogging. The orientation of the spine was reconstructed using several filters, including a novel filter developed specifically for high performance at low sampling frequencies. Benchmarking against optical motion capture, we developed a model showing that the error of all tested filters depends exponentially on the sampling frequency, with the optimal filter gains showing a similar exponential relationship. Using this model of error, we developed a criterion for recommending minimum sampling frequencies for accurate motion estimates for each task, finding frequencies ranging from about 13 to 35 Hz sufficient depending on the task. Although we only studied the spine, these models should provide insight into optimizing sampling rate and filter parameters for inertial measurements in general use.

A scoping review of portable sensing for out-of-lab anterior cruciate ligament injury prevention and rehabilitation

Anterior cruciate ligament (ACL) injury and ACL reconstruction (ACLR) surgery are common. Laboratory-based biomechanical assessment can evaluate ACL injury risk and rehabilitation progress after ACLR; however, lab-based measurements are expensive and inaccessible to most people. Portable sensors such as wearables and cameras can be deployed during sporting activities, in clinics, and in patient homes. Although many portable sensing approaches have demonstrated promising results during various assessments related to ACL injury, they have not yet been widely adopted as tools for out-of-lab assessment. The purpose of this review is to summarize research on out-of-lab portable sensing applied to ACL and ACLR and offer our perspectives on new opportunities for future research and development. We identified 49 original research articles on out-of-lab ACL-related assessment; the most common sensing modalities were inertial measurement units, depth cameras, and RGB cameras. The studies combined portable sensors with direct feature extraction, physics-based modeling, or machine learning to estimate a range of biomechanical parameters (e.g., knee kinematics and kinetics) during jump-landing tasks, cutting, squats, and gait. Many of the reviewed studies depict proof-of-concept methods for potential future clinical applications including ACL injury risk screening, injury prevention training, and rehabilitation assessment. By synthesizing these results, we describe important opportunities that exist for clinical validation of existing approaches, using sophisticated modeling techniques, standardization of data collection, and creation of large benchmark datasets. If successful, these advances will enable widespread use of portable-sensing approaches to identify ACL injury risk factors, mitigate high-risk movements prior to injury, and optimize rehabilitation paradigms.

In-field assessment of change-of-direction ability with a single wearable sensor

The Agility T-test is a standardized method to measure the change-of-direction (COD) ability of athletes in the field. It is traditionally scored based on the total completion time, which does not provide information on the different CODs. Augmenting the T-test with wearable sensors provides the opportunity to explore new metrics. Towards this, data of 23 professional soccer players were recorded with a trunk-worn GNSS-IMU (Global Navigation Satellite System-Inertial Measurement Unit) device. A method for detecting the four CODs based on the wavelet-denoised antero-posterior acceleration signal was developed and validated using video data (60 Hz). Following this, completion time was estimated using GNSS ground speed and validated with the photocell data. The proposed method yields an error (mean ± standard deviation) of 0 ± 66 ms for the COD detection, - 0.16 ± 0.22 s for completion time, and a relative error for each COD duration and each sequential movement durations of less than 3.5 ± 16% and 7 ± 7%, respectively. The presented algorithm can highlight the asymmetric performance between the phases and CODs in the right and left direction. By providing a more comprehensive analysis in the field, this work can enable coaches to develop more personalized training and rehabilitation programs.

Effects of soft tissue artifacts on the calculated kinematics of the knee during walking and running

Kinematics of the knee during gait has mostly been studied using optical motion capture systems (MCS). The presence of soft tissue artifacts (STA) between the skin markers and the underlying bone presents a major impediment to obtaining a reliable joint kinematics assessment. In this study, we determined the effects of STA on the calculation of knee joint kinematics during walking and running, through the combination of high-speed dual fluoroscopic imaging system (DFIS) and magnetic resonance imaging technique. Ten adults walked and ran while data was collected simultaneously from MCS and high-speed DFIS. The study showed that measured STA underestimated knee flexion angle, but overestimated knee external and varus rotation. The absolute error values of the skin markers derived from knee flexion-extension angle, internal-external rotation, and varus-valgus rotation during walking were -3.2 ± 4.3 deg, 4.6 ± 3.1 deg, and 4.5 ± 3.2 deg respectively, and during running were -5.8 ± 5.4 deg, 6.6 ± 3.7 deg, and 4.8 ± 2.5 deg respectively. Average errors relative to the DFIS for flexion-extension angle, internal-external rotation, and varus-valgus rotation were 78 %, 271 %, 265 % during walking respectively, and were 43 %, 106 %, 200 % during running respectively. This study offers reference for the kinematic differences between MCS and high-speed DFIS, and will contribute to optimizing methods for analyzing knee kinematics during walking and running.

Face touch monitoring using an instrumented wristband using dynamic time warping and k-nearest neighbours

One of the main factors in controlling infectious diseases such as COVID-19 is to prevent touching preoral and prenasal regions. Face touching is a habitual behaviour that occurs frequently. Studies showed that people touch their faces 23 times per hour on average. A contaminated hand could transmit the infection to the body by a facial touch. Since controlling this spontaneous habit is not easy, this study aimed to develop and validate a technology to detect and monitor face touch using dynamic time warping (DTW) and KNN (k-nearest neighbours) based on a wrist-mounted inertial measurement unit (IMU) in a controlled environment and natural environment trials. For this purpose, eleven volunteers were recruited and their hand motions were recorded in controlled and natural environment trials using a wrist-mounted IMU. Then the sensitivity, precision, and accuracy of our developed technology in detecting the face touch were evaluated. It was observed that the sensitivity, precision, and accuracy of the DTW-KNN classifier were 91%, 97%, and 85% in controlled environment trials and 79%, 92%, and 79% in natural environment trials (daily life). In conclusion, a wrist-mounted IMU, widely available in smartwatches, could detect the face touch with high sensitivity, precision, and accuracy and can be used as an ambulatory system to detect and monitor face touching as a high-risk habit in daily life.

Assessment of Three-Dimensional Kinematics of High- and Low-Calibre Hockey Skaters on Synthetic ice Using Wearable Sensors

Hockey skating objective assessment can help coaches detect players’ performance drop early and avoid fatigue-induced injuries. This study aimed to calculate and experimentally validate the 3D angles of lower limb joints of hockey skaters obtained by inertial measurement units and explore the effectiveness of the on-ice distinctive features measured using these wearable sensors in differentiating low- and high-calibre skaters. Twelve able-bodied individuals, six high-calibre and six low-calibre skaters, were recruited to skate forward on a synthetic ice surface. Five IMUs were placed on their dominant leg and pelvis. The 3D lower-limb joint angles were obtained by IMUs and experimentally validated against those obtained by a motion capture system with a maximum root mean square error of 5 deg. Additionally, among twelve joint angle-based distinctive features identified in other on-ice studies, only three were significantly different (p-value < 0.05) between high- and low-calibre skaters in this synthetic ice experiment. This study thus indicated that skating on synthetic ice alters the skating patterns such that the on-ice distinctive features can no longer differentiate between low- and high-calibre skating joint angles. This wearable technology has the potential to help skating coaches keep track of the players’ progress by assessing the skaters’ performance, wheresoever.

Measurement of temporal and spatial parameters of ice hockey skating using a wearable system

Ice hockey is a dynamic and competitive sport that requires a high level of neuromuscular and cardiovascular function. An objective assessment of skating helps coaches monitor athletes' performance during training sessions and matches. This study aimed to estimate the temporal and spatial parameters of skating by proposing an optimized configuration of wearable inertial measurement units (IMUs) and validating the system compared to in-lab reference systems. Ten participants were recruited to skate on a 14 m synthetic ice surface built in a motion-capture lab. Eight original event detection methods and three more adopted from gait analysis studies were implemented to detect blades-off and skate-strikes. These temporal events were detected with high accuracy and precision using skate-mounted IMUs. Also, four novel stride length estimation methods were developed to correct the estimated skaters' position using IMUs' readouts. The stride time, contact time, stride length, and stride velocity were obtained with relative errors of 3 ± 3%, 4 ± 3%, 2 ± 6%, and 2 ± 8%, respectively. This study showed that the wearable IMUs placed on skates and pelvis enables the estimation of temporal and spatial parameters of skating with high accuracy and precision, which could help coaches monitor skaters' performance in training.

Reliability of wearable sensors-based parameters for the assessment of knee stability

Anterior cruciate ligament (ACL) rupture represents one of the most recurrent knee injuries in soccer players. To allow a safe return to sport after ACL reconstruction, standardised and reliable procedures/criteria are needed. In this context, wearable sensors are gaining momentum as they allow obtaining objective information during sport-specific and in-the-field tasks. This paper aims at proposing a sensor-based protocol for the assessment of knee stability and at quantifying its reliability. Seventeen soccer players performed a single leg squat and a cross over hop test. Each participant was equipped with two magnetic-inertial measurement units located on the tibia and foot. Parameters related to the knee stability were obtained from linear acceleration and angular velocity signals. The intraclass correlation coefficient (ICC) and minimum detectable change (MDC) were calculated to evaluate each parameter reliability. The ICC ranged from 0.29 to 0.84 according to the considered parameter. Specifically, angular velocity-based parameters proved to be more reliable than acceleration-based counterparts, particularly in the cross over hop test (average ICC values of 0.46 and 0.63 for acceleration- and angular velocity-based parameters, respectively). An exception was represented, in the single leg squat, by parameters extracted from the acceleration trajectory on the tibial transverse plane (0.60≤ICC≤0.76), which can be considered as promising candidates for ACL injury risk assessment. Overall, greater ICC values were found for the dominant limb, with respect to the non-dominant one (average ICC: 0.64 and 0.53, respectively). Interestingly, this between-limb difference in variability was not always mirrored by LSI results. MDC values provide useful information in the perspective of applying the proposed protocol on athletes with ACL reconstruction. Thus, The outcome of this study sets the basis for the definition of reliable and objective criteria for return to sport clearance after ACL injury.

Augmented Cooper test: Biomechanical contributions to endurance performance

Running mechanics are modifiable with training and adopting an economical running technique can improve running economy and hence performance. While field measurement of running economy is cumbersome, running mechanics can be assessed accurately and conveniently using wearable inertial measurement units (IMUs). In this work, we extended this wearables-based approach to the Cooper test, by assessing the relative contribution of running biomechanics to the endurance performance. Furthermore, we explored different methods of estimating the distance covered in the Cooper test using a wearable global navigation satellite system (GNSS) receiver. Thirty-three runners (18 highly trained and 15 recreational) performed an incremental laboratory treadmill test to measure their maximum aerobic speed (MAS) and speed at the second ventilatory threshold (sVT2). They completed a 12-minute Cooper running test with foot-worm IMUs and a chest-worn GNSS-IMU on a running track 1–2 weeks later. Using the GNSS receiver, an accurate estimation of the 12-minute distance was obtained (accuracy of 16.5 m and precision of 1.1%). Using this distance, we showed a reliable estimation [R² > 0.9, RMSE ϵ (0.07, 0.25) km/h] of the MAS and sVT2. Biomechanical metrics were extracted using validated algorithm and their association with endurance performance was estimated. Additionally, the high-/low-performance runners were compared using pairwise statistical testing. All performance variables, MAS, sVT2, and average speed during Cooper test, were predicted with an acceptable error (R² ≥ 0.65, RMSE ≤ 1.80 kmh⁻¹) using only the biomechanical metrics. The most relevant metrics were used to develop a biomechanical profile representing the running technique and its temporal evolution with acute fatigue, identifying different profiles for runners with highest and lowest endurance performance. This profile could potentially be used in standardized functional capacity measurements to improve personalization of training and rehabilitation programs.

K-score: A novel scoring system to quantify fatigue-related ergonomic risk based on joint angle measurements via wearable inertial measurement units

Work-related musculoskeletal disorders have been recognized as a global problem that affects millions of people annually. Fatigue is one of the main contributors to musculoskeletal disorders. Thus, this study investigated fatigue detection based on the measured body motion by wearable inertial measurement units. We quantified the body motion during manual handling tasks using a novel kinematic score (i.e., K-score), and the Rapid Entire Body Assessment (REBA). K-score and REBA were calculated using joint angles. Nevertheless, unlike REBA, K-score showed a significant correlation (Spearman's correlation coefficient of ρ(302) = 0.21, p < 0.05) with electromyography (EMG) signal amplitude, which was affected by muscle fatigue. Therefore, in-field measurement of K-score using inertial measurement units could detect the fatigue-induced change of body motion in long-duration manual handling tasks. Our proposed K-score can be used to assess fatigue-related ergonomic risk in long-term and real-world working conditions without the need for tedious EMG recording at workplaces.

Can the Eight Hop Test Be Measured with Sensors? A Systematic Review

Rehabilitation aims to increase the independence and physical function after injury, surgery, or other trauma, so that patients can recover to their previous ability as much as possible. To be able to measure the degree of recovery and impact of the treatment, various functional performance tests are used. The Eight Hop Test is a hop exercise that is directly linked to the rehabilitation of people suffering from tendon and ligament injuries on the lower limb. This paper presents a systematic review on the use of sensors for measuring functional movements during the execution of the Eight Hop Test, focusing primarily on the use of sensors, related diseases, and different methods implemented. Firstly, an automated search was performed on the publication databases: PubMed, Springer, ACM, IEEE Xplore, MDPI, and Elsevier. Secondly, the publications related to the Eight-Hop Test and sensors were filtered according to several search criteria and 15 papers were finally selected to be analyzed in detail. Our analysis found that the Eight Hop Test measurements can be performed with motion, force, and imaging sensors.

Assessment of countermovement jump with and without arm swing using a single inertial measurement unit

The countermovement vertical jump height, flight time, and jump duration are used to assess athletic performance. Force-plate and motion-capture cameras are used to estimate these parameters, yet, their application is limited to dedicated lab environments. Despite the potential of inertial measurement units (IMU) for estimating the jump height, their accuracy has not been validated. This study investigates the accuracy of our proposed method to estimate the jump height using a sacrum-mounted IMU, during countermovement jumping. Eleven individuals performed four jumps each. To obtain the jump height, we transformed the IMU readouts into anatomical planes, and double-integrated the vertical acceleration after correction for zero velocity and vertical displacement. The accuracy of jump height obtained by IMU was compared to force-plate and motion-capture cameras during jumps without arm swing (mean error (standard deviation) of 0.3(2.2) cm and 1.0(3.0) cm, and correlation coefficient of 0.83 and 0.82, respectively) and during jumps with arm swing (-1.1(2.1) cm and 0.5(1.9) cm, and 0.92 and 0.89). The correlation coefficients were high, and the errors were comparable to the difference between the jump height obtained by force-plate and cameras. Therefore, a sacrum-mounted IMU can be recommended for in-field assessment of countermovement jump with and without arm swing.

Foot angular kinematics measured with inertial measurement units: A reliable criterion for real-time gait event detection

Accurate and reliable real-time detection of gait events using inertial measurement units (IMUs) is crucial for (1) developing clinically meaningful gait parameters to differentiate normal and impaired gait or (2) creating patient-tailored gait rehabilitation strategies or control of prosthetic devices using feedback from gait phases. However, most previous studies focused only on algorithms with high temporal accuracy and neglected the importance of (1) high reliability, i.e., detecting only and all true gait events, and (2) real-time implementation. Thus, in this study, we presented a novel approach for initial contact (IC) and terminal contact (TC) detection in real-time based on the measurement of the foot orientation. Unlike foot/shank angular velocity and acceleration, foot orientation provides physiologically meaningful kinematic features corresponding to our observational recognition of IC and TC, regardless of the walking modality. We conducted an experimental study to validate our algorithm, including seven participants performing four walking/running activities. By analyzing 5,555 ICs/TCs recorded during the tests, only our algorithm achieved a sensitivity and precision of 100%. Our obtained temporal accuracy (mean ± standard deviation of errors ranging from 0 ± 3 to 6 ± 5 time samples; sampling frequency: 100 Hz) was better than or comparable to those reported in the literature. Our algorithm's performance does not depend on thresholds and gait speed/modality, and it can be used for feedback-based therapeutic gait training or real-time control of assistive or prosthetic technologies. Nevertheless, its performance for pathological gait must be validated in the future. Finally, we shared the codes and sample data on https://www.ncbl.ualberta.ca/codes.

Predicted Threshold for Seated Stability: Estimation of Margin of Stability Using Wearable Inertial Sensors

Individuals with spinal cord injury suffer from seated instability due to impaired trunk neuromuscular function. Monitoring seated stability toward the development of closed-loop controlled neuroprosthetic technologies could be beneficial for restoring trunk stability during sitting in affected individuals. However, there is a lack of (1) a biomechanical characterization to quantify the relationship between the trunk kinematics and sitting balance; and (2) a validated wearable biomedical device for assessing dynamic sitting posture and fall-risk in real-time. This study aims to: (a) determine the limit of dynamic seated stability as a function of the trunk center of mass (COM) position and velocity relative to the base of support; (b) experimentally validate the predicted limit of stability using traditional motion capture; (c) compare the predicted limit of stability with that predicted in the literature for standing and walking; and (d) validate a wearable device for assessing dynamic seated stability and risk of loss of balance. First, we used a six-segment model of the seated human body for simulation. To obtain the limit of stability, we applied forward dynamics and optimization to obtain the maximum feasible initial velocities of the trunk COM that would bring the trunk COM position to the front-end of the base-of-support for a set of initial COM positions. Second, experimental data were obtained from fifteen able-bodied individuals who maintained sitting balance while base-of-support perturbations were applied with three different amplitudes. A motion capture system and four inertial measurement units (IMUs) were used to estimate the trunk COM motion states (i.e., trunk COM position and velocity). The margin of stability was calculated as the shortest distance of the instantaneous COM motion states to those obtained as the limit of stability in the state-space plane. All experimentally obtained trunk COM motion states fell within the limit of stability. A high correlation and small root-mean-square difference were observed between the estimated trunk COM states obtained by the motion capture system and IMUs. IMU-based wearable technology, along with the predicted limit of dynamic seated stability, can estimate the margin of stability during perturbed sitting. Therefore, it has the potential to monitor the seated stability of wheelchair users affected by trunk instability.

A novel instrumented shoulder functional test using wearable sensors in patients with brachial plexus injury

BACKGROUND

Because nerve injury of muscles around the shoulder can be easily disguised by "trick movements" of the trunk, shoulder dysfunction following brachial plexus injury is difficult to quantify with conventional clinical tools. Thus, to evaluate brachial plexus injury and quantify its biomechanical consequences, we used inertial measurement units, which offer the sensitivity required to measure the trunk's subtle movements.

METHODS

We calculated 6 kinematic scores using inertial measurement units placed on the upper arms and the trunk during 9 functional tasks. We used both statistical and machine learning techniques to compare the bilateral asymmetry of the kinematic scores of 15 affected and 15 able-bodied individuals (controls).

RESULTS

Asymmetry indexes from several kinematic scores of the upper arm and trunk showed a significant difference (P < .05) between the affected and control groups. A bagged ensemble of decision trees trained with trunk and upper arm kinematic scores correctly classified all controls. All but 2 patients were also correctly classified. Upper arm scores showed correlation coefficients ranging from 0.55-0.76 with conventional clinical scores.

CONCLUSIONS

The proposed wearable technology is a sensitive and reliable tool for objective outcome evaluation of brachial plexus injury and its biomechanical consequences. It may be useful in clinical research and practice, especially in large cohorts with multiple follow-ups.