Evaluating Performance of the Single Leg Squat Exercise with a Single Inertial Measurement Unit

The single leg squat (SLS) is an important component of lower limb rehabilitation and injury risk screening tools. This study sought to investigate whether a single lumbar-worn IMU is capable of discriminating between correct and incorrect performance of the SLS. Nineteen healthy volunteers (15 males, 4 females, age: 26.09±3.98 years, height: 1.75±0.14m, body mass: 75.2±14.2kg) were fitted with a single IMU on the lumbar spine and asked to perform 10 left leg SLS. These repetitions were recorded and labelled by a chartered physiotherapist. Features were extracted from the labelled sensor data. These features were used to train and evaluate a random-forests classifier. The system achieved an average of 92% accuracy, 78% sensitivity and 97% specificity. These results indicate that a single IMU has the potential to differentiate between a correctly and incorrectly completed SLS. This may allow such devices to be used by clinicians to help track rehabilitation of patients and screen for potential injury risks. Furthermore, the classifier described may be a useful input to an exercise biofeedback application

Evaluating Performance of the Single Leg Squat Exercise with a Single Inertial Measurement Unit

The single leg squat (SLS) is an important component of lower limb rehabilitation and injury risk screening tools. This study sought to investigate whether a single lumbar-worn IMU is capable of discriminating between correct and incorrect performance of the SLS. Nineteen healthy volunteers (15 males, 4 females, age: 26.09±3.98 years, height: 1.75±0.14m, body mass: 75.2±14.2kg) were fitted with a single IMU on the lumbar spine and asked to perform 10 left leg SLS. These repetitions were recorded and labelled by a chartered physiotherapist. Features were extracted from the labelled sensor data. These features were used to train and evaluate a random-forests classifier. The system achieved an average of 92% accuracy, 78% sensitivity and 97% specificity. These results indicate that a single IMU has the potential to differentiate between a correctly and incorrectly completed SLS. This may allow such devices to be used by clinicians to help track rehabilitation of patients and screen for potential injury risks. Furthermore, the classifier described may be a useful input to an exercise biofeedback application

Reliability and Criterion Validity of the Assess2Perform Bar Sensei

The Assess2Perform Bar Sensei is a device used to measure barbell velocity for velocity-based training that has not yet been validated. The purpose of this study was to determine criterion validity and reliability of the Assess2Perform Bar Sensei in barbell back squats by comparing it against the GymAware PowerTool, a previously validated instrument. Sixteen injury-free, resistance-trained subjects (eleven males and five females) were recruited. Subjects were tested for their back squat one repetition maximum (1RM). Then, on two separate days, subjects performed two sets of three repetitions at loads of 45%, 60% and 75% 1RM. The GymAware PowerTool and Bar Sensei were attached to the barbell in similar locations for concurrent collection of mean concentric velocity (MCV) and peak concentric velocity (PCV). The Bar Sensei and PowerTool showed generally fair to poor agreement for MCV and PCV when subjects lifted 45% of 1RM (intraclass correlation;ICC 0.4–0.59), and they showed poor agreement when subjects lifted 60% and 75% of 1RM (ICC 0.3–0.4). Inter-repetition/within-set reliability for the Bar Sensei ranged between ICC = 0.273–0.451 for MCV and PCV compared to the far more reliable PowerTool (ICC = 0.651–0.793). Currently, the Bar Sensei is not a reliable or valid tool for measuring barbell velocity in back squats

Validity and reliability of a wearable inertial sensor to measure velocity and power in the back squat and bench press

Orange, ST, Metcalfe, JW, Liefeith, A, Marshall, P, Madden, LA, Fewster, CR, and Vince, RV. Validity and reliability of a wearable inertial sensor to measure velocity and power in the back squat and bench press. J Strength Cond Res 33(9): 2398-2408, 2019-This study examined the validity and reliability of a wearable inertial sensor to measure velocity and power in the free-weight back squat and bench press. Twenty-nine youth rugby league players (18 ± 1 years) completed 2 test-retest sessions for the back squat followed by 2 test-retest sessions for the bench press. Repetitions were performed at 20, 40, 60, 80, and 90% of 1 repetition maximum (1RM) with mean velocity, peak velocity, mean power (MP), and peak power (PP) simultaneously measured using an inertial sensor (PUSH) and a linear position transducer (GymAware PowerTool). The PUSH demonstrated good validity (Pearson's product-moment correlation coefficient [r]) and reliability (intraclass correlation coefficient [ICC]) only for measurements of MP (r = 0.91; ICC = 0.83) and PP (r = 0.90; ICC = 0.80) at 20% of 1RM in the back squat. However, it may be more appropriate for athletes to jump off the ground with this load to optimize power output. Further research should therefore evaluate the usability of inertial sensors in the jump squat exercise. In the bench press, good validity and reliability were evident only for the measurement of MP at 40% of 1RM (r = 0.89; ICC = 0.83). The PUSH was unable to provide a valid and reliable estimate of any other criterion variable in either exercise. Practitioners must be cognizant of the measurement error when using inertial sensor technology to quantify velocity and power during resistance training, particularly with loads other than 20% of 1RM in the back squat and 40% of 1RM in the bench press

Wearable inertial sensors and range of motion metrics in physical therapy remote support

Abstract. The practice of physiotherapy diagnoses patient ailments which are often treated by the daily repetition of prescribed physiotherapeutic exercise. The effectiveness of the exercise regime is dependent on regular daily repetition of the regime and the correct execution of the prescribed exercises. Patients often have issues learning unfamiliar exercises and performing the exercise with good technique. This design science research study examines a back squat classifier design to appraise patient exercise regime away from the physiotherapy practice. The scope of the exercise appraisal is limited to one exercise, the back squat. Kinematic data captured with commercial inertial sensors is presented to a small group of physiotherapists to illustrate the potential of the technology to measure range of motion (ROM) for back squat appraisal. Opinions are considered from two fields of physiotherapy, general musculoskeletal and post-operative rehabilitation. While the exercise classifier is considered not suitable for post-operative rehabilitation, the opinions expressed for use in general musculoskeletal physiotherapy are positive. Kinematic data captured with gyroscope sensors in the sagittal plane is analysed with Matlab to develop a method for back squat exercise recognition and appraisal. The artefact, a back squat classifier with appraisal features is constructed from Matlab scripts which are proven to be effective with kinematic data from a novice athlete

Inertial sensors-based lower-limb rehabilitation assessment: A comprehensive evaluation of gait, kinematic and statistical metrics

Analysis of biomechanics is frequently used in both clinical and sporting practice in order to assess human motion and their performance of defined tasks. Whilst camera-based motion capture systems have long been regarded as the ‘Gold-standard’ for quantitative movement-based analysis, their application is not without limitations as regards potential sources of variability in measurements, high cost, and practicality of use for larger patient/subject groups. Another more practical approach, which presents itself as a viable solution to biomechanical motion capture and monitoring in sporting and patient groups, is through the use of small-size low-cost wearable Micro-ElectroMechanical Systems (MEMs)-based inertial sensors. The clinical aim of the present work is to evaluate rehabilitation progress following knee injuries, identifying a number of metrics measured via a wireless inertial sensing system. Several metrics in the time-domain have been considered to be reliable for measuring and quantifying patient progress across multiple exercises in different activities. This system was developed at the Tyndall National Institute and is able to provide a complete and accurate biomechanics assessment without the constraints of a motion capture laboratory. The results show that inertial sensors can be used for a quantitative assessment of knee joint mobility, providing valuable information to clinical experts as regards the trend of patient progress over the course of rehabilitation

Are tibial angles measured with inertial sensors useful surrogates for frontal plane projection angles using 2-dimensional video analysis during single leg squat tasks? A reliability and agreement analysis in elite football (soccer) players

During single leg squats (SLS), tibial angle (TA) quantification using inertial measurement units (IMU) may offer a practical alternative to frontal plane projection angle (FPPA) measurement using 2-dimensional (2D) video analysis. This study determined: (i) the reliability of IMUs and 2D video analysis for TA measurement, and 2D video analysis for FPPA measurement; (ii) the agreement between IMU TA and both 2D video TA and FPPA measurements during single leg squats in elite footballers. 18 players were tested on consecutive days. Absolute TA (ATA) and relative TA (RTA) were measured with IMUs. ATA and FPPA were measured concurrently using 2D video analysis. Within-session reliability for all measurements varied across days (intraclass correlation coefficient (ICC) range=0.27–0.83, standard error of measurement (SEM) range=2.12–6.23°, minimal detectable change (MDC) range=5.87–17.26°). Between-sessions, ATA reliability was good for both systems (ICCs=0.70–0.74, SEMs=1.64–7.53°, MDCs=4.55–7.01°), while IMU RTA and 2D FPPA reliability ranged from poor to good (ICCs=0.39–0.72, SEMs=2.60–5.99°, MDCs=7.20–16.61°). All limits of agreement exceeded a 5° acceptability threshold. Both systems were reliable for between-session ATA, although agreement was poor. IMU RTA and 2D video FPPA reliability was variable. For SLS assessment, IMU derived TAs are not useful surrogates for 2D video FPPA measures in this population

Velocity-Based Training: Current Concepts and Future Directions

Topics in Exercise Science and Kinesiology 3(1): Article 1, 2022. Velocity-based training (VBT) is a current approach to resistance training that relies on measured bar, implement, and/or athlete speed to formulate and adjust training for both long-term programming and daily training sessions. Relying on a number of available tools of varying levels of accuracy, VBT can help the strength and conditioning specialist and/or the rehabilitation professional to not only better predict strength and power over time, but also to adjust training loads in order to maximize training response in a given session. While the appeal and price points of available technology in the marketplace have made VBT more accessible than ever, a real need exists to establish the efficacy of the approach in practical settings

Concurrent Validity of the Inertial Measurement Unit Vmaxpro in Vertical Jump Estimation

The aim of this study was to evaluate if the inertial measurement unit (IMU) Vmaxpro is a valid device to estimate vertical jump height (VJH) when compared to a motion capture system (MoCAP). Thirteen highly trained female volleyball players participated in this study which consisted of three sessions. After a familiarization session, two sessions comprised a warm-up followed by ten countermovement jumps, resting two min between each attempt. Jump height was measured simultaneously by Vmaxpro using take-off velocity and MoCAP using center-of-mass vertical excursion. Results show significant differences in jump height between devices (10.52 cm; p < 0.001; ES = 0.9), a very strong Spearman’s correlation (rs = 0.84: p < 0.001), and a weak concordance correlation coefficient (CCC = 0.22; ρ = 0.861; Cb= 0.26). Regression analysis reveals very high correlations, high systematic error (8.46 cm), and a nonproportional random error (SEE = 1.67 cm). Bland–Altman plots show systematic error (10.6 cm) with 97.3 % of the data being within the LoA. In conclusion, Vmaxpro can be considered a valid device for the estimation of VJH, being a cheaper, portable, and manageable alternative to MoCAP. However, the magnitude of systematic error discourages its use where indistinguishable data from Vmaxpro and MoCAP are used unless the corresponding specific fitting equation is applied.This work was supported by Generalitat Valenciana (grant number GV/2021/098)