Reliability of Measuring Leg Segments and Joint Angles Using Smartphones during Aquatic Exercise
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Objectives: Aquatic therapy is a significant intervention method for both patients and healthy individuals. However, in clinicalpractice, quantitative measurements are rarely applied in aquatic therapy due to the disadvantages of submerging expensiveinstruments in water. In this study, we used readily available smartphones and armbands to measure leg segments andjoint angles during aquatic gait and evaluated the reliability of these measurements. Methods: Waterproof smartphones werestrapped to the trunk, thighs, and shanks of 19 healthy young adults using armbands. The angles of the trunk, thigh, andshank segments were measured during aquatic gait. The measurements were repeated 1 day later. The data were analyzed toobtain the angles of the hip and knee joints. Results: Measurement repeatability, calculated using the intraclass correlationcoefficient (ICC), was the highest for the shank segment range of motion (ROM) (first 46.79° ± 5.50°, second 50.12° ± 9.98°,ICC = 0.78). There was high agreement in trunk segment ROM (first 6.36° ± 1.42°, second 4.29° ± 1.83°, ICC = 0.73), thighsegment ROM (first 33.49° ± 5.18°, second 37.31° ± 8.70°, ICC = 0.62), and knee joint ROM (first 52.43° ± 11.26°, second62.19° ± 16.65°, ICC = 0.68) and fair agreement in hip joint ROM (first 34.60°±4.71°, second 37.80° ± 7.84°, ICC = 0.59). Conclusions: Smartphones can be used to reliably measure leg segments and joint angles during aquatic gait, providing asimpler method for obtaining these measurements and enabling the wider use of aquatic motion analysis in clinical practiceand research.
Abstract
Objectives: Aquatic therapy is a significant intervention method for both patients and healthy individuals. However, in clinicalpractice, quantitative measurements are rarely applied in aquatic therapy due to the disadvantages of submerging expensiveinstruments in water. In this study, we used readily available smartphones and armbands to measure leg segments andjoint angles during aquatic gait and evaluated the reliability of these measurements. Methods: Waterproof smartphones werestrapped to the trunk, thighs, and shanks of 19 healthy young adults using armbands. The angles of the trunk, thigh, andshank segments were measured during aquatic gait. The measurements were repeated 1 day later. The data were analyzed toobtain the angles of the hip and knee joints. Results: Measurement repeatability, calculated using the intraclass correlationcoefficient (ICC), was the highest for the shank segment range of motion (ROM) (first 46.79° ± 5.50°, second 50.12° ± 9.98°,ICC = 0.78). There was high agreement in trunk segment ROM (first 6.36° ± 1.42°, second 4.29° ± 1.83°, ICC = 0.73), thighsegment ROM (first 33.49° ± 5.18°, second 37.31° ± 8.70°, ICC = 0.62), and knee joint ROM (first 52.43° ± 11.26°, second62.19° ± 16.65°, ICC = 0.68) and fair agreement in hip joint ROM (first 34.60°±4.71°, second 37.80° ± 7.84°, ICC = 0.59). Conclusions: Smartphones can be used to reliably measure leg segments and joint angles during aquatic gait, providing asimpler method for obtaining these measurements and enabling the wider use of aquatic motion analysis in clinical practiceand research.
참고문헌 (30)
- Mangia AL, "The use of IMMUs in a water environment : instrument validation and application of 3D multi-body kinematic analysis in medicine and sport", Sensors(Basel), 17(4), pp.927~ (2017)
- Fantozzi S, "Gait kinematic analysis in water using wearable inertial magnetic sensors", PLoS One, 10(9), pp.e0138105~ (2015)[DOI]
- Mercer JA, "Muscle activity during running with different body-weight-support mechanisms : aquatic environment versus body-weightsupport treadmill", J Sport Rehabil, 23(4), pp.300~306 (2014)
- Jung T, "The influence of water depth on kinematic and spatiotemporal gait parameters during aquatic treadmill walking", Sports Biomech, 18(3), pp.297~307 (2019)
- Dolbow DR, "Oxygen consumption, heart rate, rating of perceived exertion, and systolic blood pressure with water treadmill walking", J Aging Phys Act, 16(1), pp.14~23 (2008)
- Nakazawa K, "Medicine and science in aquatic sports", pp.28~34 (1994), S. Karger AG
- Murray JM, "Determination of the physiological effects of unloaded treadmill exercise", Cardiopulm Phys Ther J, 4(2), pp.13~16 (1993)
- Skelton DA, "Exercise for falls management : rationale for an exercise programme aimed at reducing postural instability", Physiother Theory Pract, 15(2), pp.105~120 (1999)
- Alikhajeh Y, "Effects of hydrotherapy in static and dynamic balance among elderly men", Procedia Soc Behav Sci, 46, pp.2220~2224 (2012)
- Silsupadol P, "Reliability and validity of a smartphone-based assessment of gait parameters across walking speed and smartphone locations : body, bag, belt, hand, and pocket", Gait Posture, 58, pp.516~522 (2017)
- Masumoto K, "Physiological and perceptual responses to backward and forward treadmill walking in water", Gait Posture, 29(2), pp.199~203 (2009)
- Ceseracciu E, "Markerless analysis of front crawl swimming", J Biomech, 44(12), pp.2236~2242 (2011)
- Cortesi M, "Effects of distance specialization on the backstroke swimming kinematics", J Sports Sci Med, 11(3), pp.526~532 (2012)
- McCabe CB, "Kinematic differences between front crawl sprint and distance swimmers at a distance pace", J Sports Sci, 30(6), pp.601~608 (2012)
- Tamburella F, "Walking in water and on land after an incomplete spinal cord injury", Am J Phys Med Rehabil, 92(10 Suppl 2), pp.e4~e15 (2013)
- Silvatti AP, "Comparison of different camera calibration approaches for underwater applications", J Biomech, 45(6), pp.1112~1116 (2012)
- Silvatti AP, "Quantitative underwater 3D motion analysis using submerged video cameras : accuracy analysis and trajectory reconstruction", Comput Methods Biomech Biomed Engin, 16(11), pp.1240~1248 (2013)
- Magalhaes FA, "Effectiveness of an automatic tracking software in underwater motion analysis", J Sports Sci Med, 12(4), pp.660~667 (2013)
- Mooney R, "Analysis of swimming performance : perceptions and practices of US-based swimming coaches", J Sports Sci, 34(11), pp.997~1005 (2016)
- Masumoto K, "Biomechanics of human locomotion in water : an electomyographic analysis", Exerc Sport Sci Rev, 36(3), pp.160~169 (2008)
- Buechi R, "Evidence assessing the diagnostic performance of medical smartphone apps : a systematic review and exploratory meta-analysis", BMJ Open, 7(12), pp.e018280~ (2017)[DOI]
- Longoni L, "Smartphone applications validated for joint angle measurement : a systematic review", Int J Rehabil Res, 42(1), pp.11~19 (2019)
- Polechonski J, "Applicability of smartphone for dynamic postural stability evaluation", Biomed Res Int, 2019, pp.9753898~ (2019)
- 이대희, "스마트폰을 이용한 걸음걸이 시 다리분절과 관절 각도 측정의 신뢰도연구", 한국정밀공학회지, 36(3), pp.293~300 (2019), 한국정밀공학회[DOI]
- Furrer M, "Validation of a smartphone-based measurement tool for the quantification of level walking", Gait Posture, 42(3), pp.289~294 (2015)
- "Samsung Galaxy S" (2021)[URL]
- Cicchetti DV, "Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology", Psychol Assess, 6(4), pp.284~290 (1994)
- Lugade V, "Validity of using tri-axial accelerometers to measure human movement. Part I: posture and movement detection", Med Eng Phys, 36(2), pp.169~176 (2014)
- Fortune E, "Validity of using tri-axial accelerometers to measure human movement. Part II: step counts at a wide range of gait velocities", Med Eng Phys, 36(6), pp.659~669 (2014)
- Barela AM, "Biomechanical characteristics of adults walking in shallow water and on land", J Electromyogr Kinesiol, 16(3), pp.250~256 (2006)