Evaluating the validity and reliability of inertial measurement units for determining knee and trunk kinematics during athletic landing and cutting movements

Chia, Lionel; Andersen, Jordan; McKay, Marnee J.; Sullivan, Justin; Megalaa, Thomas; Pappas, Evangelos

doi:10.1016/j.jelekin.2021.102589

Cited by 17 publications

(13 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The findings of this systematic review support the assessment of trunk biomechanics in individuals with OA, PFP, or ACLR to identify possible targets for rehabilitation, especially for those with chronic pain. Reliable, valid, and time- and cost-effective field-based assessments of biomechanics can be performed through two-dimensional motion capture [ 144 – 149 ] and wearable inertial measurement units (IMU) [ 150 , 151 ]. To target altered trunk kinematics in the sagittal and frontal planes, clinicians can consider interventions like progressive resistance training [ 152 ], virtual reality training [ 153 ], and motor feedback control using IMUs, visual or verbal feedback [ 154 – 156 ].…”

Section: Discussionmentioning

confidence: 99%

Trunk Biomechanics in Individuals with Knee Disorders: A Systematic Review with Evidence Gap Map and Meta-analysis

et al. 2022

Self Cite

View full text Add to dashboard Cite

Background The trunk is the foundation for transfer and dissipation of forces throughout the lower extremity kinetic chain. Individuals with knee disorders may employ trunk biomechanical adaptations to accommodate forces at the knee or compensate for muscle weakness. This systematic review aimed to synthesize the literature comparing trunk biomechanics between individuals with knee disorders and injury-free controls. Methods Five databases were searched from inception to January 2022. Observational studies comparing trunk kinematics or kinetics during weight-bearing tasks (e.g., stair negotiation, walking, running, landings) between individuals with knee disorders and controls were included. Meta-analyses for each knee disorder were performed. Outcome-level certainty was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE), and evidence gap maps were created. Results A total of 81 studies investigating trunk biomechanics across six different knee disorders were included (i.e., knee osteoarthritis [OA], total knee arthroplasty [TKA], patellofemoral pain [PFP], patellar tendinopathy [PT], anterior cruciate ligament deficiency [ACLD], and anterior cruciate ligament reconstruction [ACLR]). Individuals with knee OA presented greater trunk flexion during squatting (SMD 0.88, 95% CI 0.58–1.18) and stepping tasks (SMD 0.56, 95% CI 0.13–.99); ipsilateral and contralateral trunk lean during walking (SMD 1.36; 95% CI 0.60–2.11) and sit-to-stand (SMD 1.49; 95% CI 0.90–2.08), respectively. Greater trunk flexion during landing tasks in individuals with PFP (SMD 0.56; 95% CI 0.01–1.12) or ACLR (SMD 0.48; 95% CI 0.21–.75) and greater ipsilateral trunk lean during single-leg squat in individuals with PFP (SMD 1.01; 95% CI 0.33–1.70) were also identified. No alterations in trunk kinematics of individuals with TKA were identified. Evidence gap maps outlined the lack of investigations for individuals with PT or ACLD, as well as for trunk kinetics across knee disorders. Conclusion Individuals with knee OA, PFP, or ACLR present with altered trunk kinematics in the sagittal and frontal planes. The findings of this review support the assessment of trunk biomechanics in these individuals in order to identify possible targets for rehabilitation and avoidance strategies. Trial registration: PROSPERO registration number: CRD42019129257.

show abstract

Section: Discussionmentioning

confidence: 99%

Trunk Biomechanics in Individuals with Knee Disorders: A Systematic Review with Evidence Gap Map and Meta-analysis

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…There were substantial differences in the accuracy metrics used across studies, making it challenging to compare the performance of different approaches. IMU-based studies reported root mean square errors (RMSEs) of 1.1 - 6.5 deg for knee flexion angle estimation [41, 26, 37, 45] and 3.3 - 10.9 deg for knee abduction angle estimation [41, 26, 45]. The accuracy of knee abduction angle estimation was poor considering the small knee abduction range of motion.…”

Section: Resultsmentioning

confidence: 99%

“…Eleven studies primarily used physics-based modeling. Integration of gyroscope data was combined with several drift compensation methods to estimate the sensor and body segment orientation in eight investigations [37, 38, 41, 44-46, 68, 74], and seven of these studies used the relative orientation between two segments to derive joint angles [37, 41, 44-46, 68, 74]. Only one study used musculoskeletal modeling, which estimated the GRF by simulating 25 artificial muscle-like actuators placed under each foot [55].…”

Section: Resultsmentioning

confidence: 99%

“…Sensing approaches are IMU [26,[29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48], depth camera [27,[49][50][51][52][53][54][55], RGB camera [56][57][58][59], EMG [60,61], pressure insole [62], soft fabric sensor [63], and multiple sensors [28,[64][65][66][67][68][69][70][71][72][73][74].…”

Section: Target Motions and Biomechanical Parametersmentioning

confidence: 99%

See 1 more Smart Citation

Towards Out-of-Lab Anterior Cruciate Ligament Injury Prevention and Rehabilitation Assessment: A Review of Portable Sensing Approaches

Tan

Gatti

Fan

et al. 2022

Preprint

View full text Add to dashboard Cite

Anterior cruciate ligament (ACL) injury and ACL reconstruction (ACLR) surgery are common. Many ACL-injured subjects develop osteoarthritis within a decade of injury, a major cause of disability without cure. Laboratory-based biomechanical assessment can evaluate ACL injury risk and rehabilitation progress after ACLR; however, lab-based measurements are expensive and inaccessible to a majority of people. Portable sensors such as wearables and cameras can be deployed during sporting activities, in clinics, and in patient homes for biomechanical assessment. 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 ACL injury prevention training, evaluation of ACL reconstructions, and return-to-sport decision making. 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 (IMUs), 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 using sophisticated modeling techniques to enable more accurate assessment along with 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.

show abstract

“…In other types of exercise different from pedaling, they have demonstrated reliability and validity [ 32 ]; however, there are other works such as the review of Poitras et al [ 31 ] in which they speak of a lower validity for the measurement of abduction/adduction movements with respect to flexion movements. Chia et al [ 35 ], despite supporting their reliability and validity, suggest the need for continuous validation and improvement of IMU systems, as well as a methodological improvement to further reduce measurement errors. Therefore, future research needs to explore the validity and reliability of measurements collected by Leomo outside the sagittal plane.…”

Section: Discussionmentioning

confidence: 99%

Validity and Reliability of the Leomo Motion-Tracking Device Based on Inertial Measurement Unit with an Optoelectronic Camera System for Cycling Pedaling Evaluation

Plaza-Bravo

Mateo‐March

Sanchis-Sanchis

et al. 2022

IJERPH

View full text Add to dashboard Cite

Background: The use of inertial measurement sensors (IMUs), in the search for a more ecological measure, is spreading among sports professionals with the aim of improving the sports performance of cyclists. The kinematic evaluation using the Leomo system (TYPE-R, Leomo, Boulder, CO, USA) has become popular. Purpose: The present study aimed to evaluate the reliability and validity of the Leomo system by measuring the angular kinematics of the lower extremities in the sagittal plane during pedaling at different intensities compared to a gold-standard motion capture camera system (OptiTrack, Natural Point, Inc., Corvallis, OR, USA). Methods: Twenty-four elite cyclists recruited from national and international cycling teams performed two 6-min cycles of cycling on a cycle ergometer at two different intensities (first ventilatory threshold (VT1) and second ventilatory threshold (VT2)) in random order, with a 5 min rest between intensity conditions. The reliability and validity of the Leomo system versus the motion capture system were evaluated. Results: Both systems showed high validity and were consistently excellent in foot angular range Q1 (FAR (Q1)) and foot angular range (FAR) (ICC-VT1 between 0.91 and 0.95 and ICC-VT2 between 0.88 and 0.97), while the variables leg angular range (LAR) and pelvic angle showed a modest validity (ICC-VT1 from 0.52 to 0.71 and ICC-VT2 between 0.61 and 0.67). Compared with Optitrack, Leomo overestimated all the variables, especially the LAR and pelvic angle values, in a range between 12 and 15°. Conclusions: Leomo is a reliable and valid tool for analyzing the ranges of motion of the cyclist’s lower limbs in the sagittal plane, especially for the variables FAR (Q1) and FAR. However, its systematic error for FAR and Pelvic Angle values must be considered in sports performance analysis.

show abstract

Evaluating the validity and reliability of inertial measurement units for determining knee and trunk kinematics during athletic landing and cutting movements

Cited by 17 publications

References 31 publications

Trunk Biomechanics in Individuals with Knee Disorders: A Systematic Review with Evidence Gap Map and Meta-analysis

Trunk Biomechanics in Individuals with Knee Disorders: A Systematic Review with Evidence Gap Map and Meta-analysis

Towards Out-of-Lab Anterior Cruciate Ligament Injury Prevention and Rehabilitation Assessment: A Review of Portable Sensing Approaches

Validity and Reliability of the Leomo Motion-Tracking Device Based on Inertial Measurement Unit with an Optoelectronic Camera System for Cycling Pedaling Evaluation

Contact Info

Product

Resources

About