Biomechanics of Human Motion and Its Clinical Applications: Instrumented Gait Analysis
Abstract
1. Introduction
2. Historical Overview of Clinical Gait Analysis
3. Methods and Validation; Applications in Clinical Gait Analysis
3.1. Marker-Based Clinical Gait Analysis
3.2. Markerless-Based Clinical Gait Analysis
Accuracy: (i) how close the values of a given system are to the standard against which it is measured, and (ii) in this context, it refers to absolute agreement and one would be looking for differences, e.g., error (°), root mean square error, etc., that have been measured.
Validity: (i) assume concurrent validity where two methods are compared simultaneously when measuring relationships between variables, (ii) correlations between the two methods are determined, with high or excellent correlations, e.g., Pearson’s r, r > 0.75, between the two systems measures confirming concurrent validity, and (iii) in this context, validity refers to relative agreement,
Inter-trial reliability: Test–retest reliability of how stable measurements are when conditions remain unchanged over time,
Inter-rater reliability: consistency of measurements made by different raters/systems,
Intra-session reliability: consistency of measurements made by the same rater/system in a series of measurements made under the same conditions[34]
3.3. Inertial Measurement Unit (IMUs)
4. Additional Comments on Clinical Gait Analysis
- Determine the severity of disease or injury, i.e., the assessment or evaluation.
- To select from treatment options.
- To monitor progress following intervention or in its absence.
- The measured parameters must correlate well with the patient’s functional capacity.
- The measured parameters must not be directly observable and semiquantifiable by the physician or therapist.
- The measured parameters must clearly distinguish between normal and abnormal.
- The measurement technique must not significantly alter the performance of the evaluated activity.
- The measurement must be accurate and reproducible.
- The results must be communicated in a form that is readily identifiable in a physical or physiological analog.
5. What the Reader Can Expect in This Special Issue
5.1. Marker-Based MOCAP
5.2. Inertial Measurement Units
5.3. Modeling
5.4. Machine Learning
5.5. Application of Plantar Pressure Measures to Characterize Antalgic Gait Associated with Hallux Valgus and Use of Gait Analysis to Study the Effects of Muscle Fatigue on Locomotion
6. Conclusions
- The measured parameters must correlate well with the patient’s functional capacity.
- The measured parameters must not be directly observable and semiquantifiable by the physician or therapist.
- The measured parameters must clearly distinguish between normal and abnormal.
- The measurement technique must not significantly alter the performance of the evaluated activity.
- The measurement must be accurate and reproducible.
- The results must be communicated in a form that is readily identifiable in a physical or physiological analog.
Author Contributions
Funding
Institutional Review Board Statement
Acknowledgments
Conflicts of Interest
References
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Alderink, G.; Õunpuu, S. Biomechanics of Human Motion and Its Clinical Applications: Instrumented Gait Analysis. Bioengineering 2025, 12, 1076. https://doi.org/10.3390/bioengineering12101076
Alderink G, Õunpuu S. Biomechanics of Human Motion and Its Clinical Applications: Instrumented Gait Analysis. Bioengineering. 2025; 12(10):1076. https://doi.org/10.3390/bioengineering12101076
Chicago/Turabian StyleAlderink, Gordon, and Sylvia Õunpuu. 2025. "Biomechanics of Human Motion and Its Clinical Applications: Instrumented Gait Analysis" Bioengineering 12, no. 10: 1076. https://doi.org/10.3390/bioengineering12101076
APA StyleAlderink, G., & Õunpuu, S. (2025). Biomechanics of Human Motion and Its Clinical Applications: Instrumented Gait Analysis. Bioengineering, 12(10), 1076. https://doi.org/10.3390/bioengineering12101076