Type of Article:  Original Research

Volume 8; Issue 5 (October 2020)

Page No.: 3602-3608

DOI: https://dx.doi.org/10.16965/ijpr.2020.151


Howe Liu *1,  Yasser Salem 2, Jingjie Zhou 3, Clayton Holmes 4, Myla Quiben 5.

*1,2,5 Department of Physical Therapy, University of North Texas Health Science Center, Fort Worth, Texas, USA.

3 Department of Rehabilition Service, Xuzhou Rehabilitation Hospital, Xuzhou, China.

4 School of Physical Therapy, Arkansas College of Healthcare Education, Fort Smith, AR. USA.

Corresponding Author: Howe Liu,  MPT, PhD, MS, MD, Department of Physical Therapy, University of North Texas Health Science Center, 3500 Camp Bowie Blvd. Fort Worth, Texas 76107, USA. E-Mail:  Howe.Liu@unthsc.edu


Background: Singe leg stance (SLS) is a commonly used assessment of balance, but there is lack of knowledge of how different body part may be involved in the SLS maintenance.  The purpose of this study was to utilize small inertial measurement unit (IMUs) to investigate how different body segments respond during static SLS.

Methods: This was a cross-sectional study with two IMU sensors utilized to compare two body locations. The sensors were placed at two flat areas – on L4-5 spinous processes for the trunk segment, and at the left popliteal fossa immediately below the knee joint line for the leg segment. All subjects recruited had the left leg as the non-dominant leg. These subjects were asked to perform a SLS on a flat hard surface with their non-dominant leg. Subjects held this position for 30 seconds, while data of body sway parameters (range, angular velocity, and acceleration) were recorded and transmitted wirelessly to a computer for storage and analysis.

Results: Compared with the leg sway, the trunk displaying a larger range in faster speed and greater acceleration than the leg primarily in the sagittal (anterior-posterior) direction (all p <.05). Also, quicker speed in axial plane, and greater acceleration in both axial and frontal planes were observed in trunk than in leg (p <.05); but no obvious differences were identified in range of sway in these two planes (P>.05).

Conclusions. During SLS on the non-dominant left leg, the whole body stays more toward left in frontal and axial planes but sways more in sagittal plane. These data may provide baseline information for future studies in more body segments and in elderly people as well.

Key Words: body segments, balance, inertial sensor, leg, trunk, 3-D planes.


[1]. Springer BA, Marin R, Cyhan T, et al. Normative values for the unipedal stance test with eyes open and closed. J Geriatr Phys Ther. 2007; 30 (1):8-15.
[2]. Promsri A, Haid T, Federolf PA. How does lower limb dominance influence postural control movements during single leg stance? Hum Movement Sci.2018; 58:165-174.
[3]. Lord SR, Sherrington C, Menz HB, Close JCT. Falls in Older People: Risk Factors and Strategies for Prevention, 2nd Edition. Pages 1-395. Cambridge University Press; 2007.
[4]. Chiovetto E, Patane L, Pozzo T. Variant and invariant features characterizing natural and reverse whole-body pointing movements. Exp Brain Res. 2012; 218(3):419-431.
[5]. Hettich G, Asslander L, Gollhofer A, Mergner T. Human hip-ankle coordination emerging from multisensory feedback control. Hum Movement Sci. 2014; 37:123-146.
[6]. Jafari H, Pauelsen M, Roijezon U, Nyberg L, Nikolakopoulos G, Gustafsson T. On Internal Modeling of the upright postural control in elderly. 2018 IEEE International Conference on Robotics and Biomimetics, ROBIO 20182 July 2018, Article number 8665209, Pages 231-236.
[7]. Wu G. Age-related differences in body segmental movement during perturbation stance in humans. Clin Biomech. 1998; 13(4-5): 300-307.
[8]. Yu JH, Hong JH, Kim JS, Nam Y, Ryu JW, Lee DY, et al. Change of muscle activities in trunk, hip and leg muscles according to variable standing posture. Int J Appl Eng Res. 2014; 9(21):8433-8440.
[9]. Bohannon RW. A descriptive met-analysis of data from individuals at least 60 years of age. Top Geriatr Rehabil. 2006; 22(1):70-77.
[10]. Anderson SO, Atkeson CG, Hodgins JK. Coordinating feet in bipedal balance. Proceedings of the 2006 6th IEEE-RAS International Conference on Humanoid Robots, HUMANOIDS2006, Article number 4115669;624-628.
[11]. Promsri A, Haid T, Federolf PA. Complexity, composition, and control of bipedal balance movement as the postural control system adapts to unstable support surface or altered feet positions. Neurosci. 2020; 430:113-124.
[12]. Bonora G, Mancini M, Carpinella L, Chiari L, Ferrarin M, Nutt JG, et al. Investigation of Anticipatory Postural Adjustments during One-Leg Stance Using Inertial Sensors: Evidence from Subjects with Parkinsonism. Front Neurol. 2017. July 25.
PMid:28790972 PMCid:PMC5524831
[13]. Oliveira MR, Vieira ER, Gil AWO, Fernandes KBP, Teixeira DC, Amorim CF, et al. One-legged stance sway of older adults with and without falls. PLoS ONE. 2018; 13(9): e0203887.
PMid:30222769 PMCid:PMC6141084
[14]. Karlsson A, Frykberg G. Correlation between force plate measures for assessment of balance. Clin Biotech. 2000; 15(5):365-369.
[15]. Lee CH, Sun TL. Evaluation of postural stability based on a force plate and inertial sensor during static balance measurements. J Physiol Anthropol. 2018; 37:27.
PMid:30545421 PMCid:PMC6293511
[16]. Seimetz C, Tan D, Katayama R, Lockhart T. A comparison between methods of measuring postural stability: Force plates versus accelerometers. Biomed Sci Instrum. 2012; 48:386-392.
[17]. Ma CZH, Wong DWC, Lam WK, Wan A, Lee W. Balance improvement effects of biofeedback systems with state-of-the-art wearable sensors: a systematic review. Sensors. 2016; 14:434.
PMid:27023558 PMCid:PMC4850948
[18]. Gazit E, Buchman AS, Dawe R, Curran TA, Mirelman A, Giladi N, et al. What happens before the first step? A new approach to quantifying gait initiation using a wearable sensor. Gait Posture. 2020; 76:128-135.
[19]. Gordt K, Gerhardy T, Najafi B, Schwenk M. Effects of wearable sensor-based balance and gait training on balance, gait, and functional performance in healthy and patient populations: a systematic review and meta-analysis of randomized controlled trials. Gerontol. 2018;64:74-89.
[20]. Ghislieri M, Gastaldi L, Pastorelli S, Tadano S, Agostini V. Wearable inertial sensors to assess standing balance: a systematic review. Sensor. 2019;19:4075.
PMid:31547181 PMCid:PMC6806601
[21]. Noamani A, Nazarahari M, Lewicke J, Vette AH, Rouhani H. Validity of using wearable inertial sensors for assessing the dynamics of standing balance. Med Eng Phys. 2020; 77:53-59.
[22]. Tanaka T, Hashimoto N, Nakata M, Ito T, Ino S, Ifukube T. Analysis of toe pressures under the foot while dynamic standing on one foot in healthy subjects: J Orthop Sports Phys Ther. 1996; 3:188-193.
[23]. Rethanya P, Babu KY, Mohanraj KG. 2018. Assessment of flat foot by plantar arch index using footprint in aged population. Drug Invent Today. 2018. 10(11):2142-2145.
[24]. Liu T, Inoue Y, Shibata K. A wearable sensor system for human motion analysis and human robot control. 2006 IEEE International Conference on Robotics and Biomimetics, ROBIO 20062006, Article number 4141837, 2006; Pages 43-48.
[25]. Poitras I, Dupuis F, Bielmann M, Campeau-Lecours A, Mercier C, Bouyer LJ, et al. Validity and reliability of wearable sensors for joint angle estimation: A systematic review. Sensors. 2019; 19:1555.
PMid:30935116 PMCid:PMC6479822
[26]. Kanamiya Y, Ota S, Sato D. Ankle and hip balance control on robotics and automations. Proceeding – IEEE International Conference on Robotics and Automation. 2010. DOI: 10.1109/ROBOT.2010.5509785.
[27]. Dutt-Mazumder A, Challis J, Newell K. Maintenance of postural stability as a function of tilted base of support: Human movement science. 2016; 48:91-101.
[28]. Bigoni M, Tarati M, Gandolla M, Augusti CA, Pedrocchi A, Torre AL, et al. Balance in young male soccer players: dominant versus non-dominant leg. Sport Sci Health. 2017; 13:253-258.
[29]. Newmann DA. Kinesiology of the Musculoskeletal System: Foundations for Rehabilitations. 2nd edition. Mosby, 2009.
[30]. Günther M, Wagner H. Dynamics of quiet human stance: computer simulations of a triple inverted pendulum model. Computer methods in biomechanics and biomedical engineering 8:819-34.

Cite this article: Howe Liu, Yasser Salem, Jingjie Zhou, Clayton Holmes, Myla Quiben. COMPARISON OF TRUNK AND LEG SWAY DURING SINGLE LEG STANCE. Int J Physiother Res 2020;8(5):3602-3608. DOI: 10.16965/ijpr.2020.151