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Minor asymmetries in gait spatiotemporal parameters can be accurately assessed using inertial measurement units
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GAIPOS-4933; No. of Pages 1 Gait & Posture xxx (2016) xxx–xxx
Contents lists available at ScienceDirect
Gait & Posture journal homepage: www.elsevier.com/locate/gaitpost
O78
Minor asymmetries in gait spatiotemporal parameters can be accurately assessed using inertial measurement units Rodrigo Martins 1,*, Ma´rcia Fernandes 2, Anto´nio Veloso 1, Ricardo Matias 1,2 1
Universidade de Lisboa, Faculdade de Motricidade Humana, Neuromechanics Research Group – Interdisciplinary Centre for the Study of Human Performance (CIPER), LBMF, Estrada da Costa, 1499-002 Cruz Queb, Lisbon, Portugal 2 Escola Superior de Sau´de, Instituto Polite´cnico de Setu´bal, Campus do Instituto Polite´cnico de Setu´bal, Estefanilha, Edifı´cio ESCE, 2914-503 Setu´bal, Portugal
Introduction: Osteoarthritis is an insidious disease that affects patients gait functionality with great expression in the ability to perform daily living activities decreasing their quality of life [1]. Early diagnosis is one of the most important factors for a favourable prognosis. Research on gait analysis in individuals with osteoarthritis points to spatiotemporal parameters, as the ones with the most significant correlation to the disease progression [2]. These parameters are normally assessed in specialised biomechanical laboratories equipped with state-of-the-art systems and highly skilled human resources. With today’s unprecedented technological evolution in sensor’s miniaturisation and computational performance, a huge opportunity arises to run a complete gait analysis, anywhere and reach a broader population. Research question: Can an ambulatory inertial measurement system detect spatial and temporal minor gait induced asymmetries in healthy subjects? Methods: A sample of 17 healthy participants (22.76 5.66 years) was recruited by means of geographic convenience. All participants were submitted to a gait asymmetry protocol in a two belt Bertec Fully Instrumented Treadmill while 3D kinematics was recorded with 17 inertial measurement units (XSens MVNBiomech) with a sample of 120 Hz in a full body configuration. After walking 30 s with both belts at 1 m/s (the average gait speed in older adults [3]) a gait protocol of 24 levels was randomly assigned to one of the belts with a speed decrease of 0.01 m/s at each 10 s. The protocol ended with a speed asymmetry of 0.24 m/s between treadmill’s belts, corresponding to the average gait
* Corresponding author. E-mail address: [email protected] (R. Martins). http://dx.doi.org/10.1016/j.gaitpost.2016.07.151 0966-6362/
asymmetry observed in individuals with an early diagnosis of osteoarthritis [1]. An automated pipeline was developed in Python to process and statistically analyse the data. Gait spatiotemporal parameters (cadence, stance time and swing time) were computed for both lower limbs and an intra-subject comparison performed in each protocol speed level. Results: The results of the Mann–Whitney U test revealed that the spatiotemporal parameter swing time showed statistically significant differences between the two lower limbs at the level 21 (p = 0.05), level 22 (p = 0.045), level 23 (p = 0.011), level 24 (p = 0.015) and level 25 (p = 0.033). Discussion: This study results show that by merging an ambulatory kinematic system with automated data analysis it is possible to detect minor gait spatiotemporal asymmetries. The asymmetry magnitude at which the statistical differences were found to be significant, was inferior to the magnitude described in patients with an early diagnosis of osteoarthritis. Further work is required but such a solution holds a great promise to evolve into a new movement disorder screening metric that can be implemented in the most widely used equipment with inertial sensors – the smartphone.
References [1] Jayalath. Int. J. Physiother. Res. 2014;2:677–80. [2] Constantinou. J. Orthop. Sports Phys. Ther. 2014;44. [3] Hollman. Gait Posture 2011;34:111–8.
GAIPOS-4933; No. of Pages 1 Gait & Posture xxx (2016) xxx–xxx
Contents lists available at ScienceDirect
Gait & Posture journal homepage: www.elsevier.com/locate/gaitpost
O78
Minor asymmetries in gait spatiotemporal parameters can be accurately assessed using inertial measurement units Rodrigo Martins 1,*, Ma´rcia Fernandes 2, Anto´nio Veloso 1, Ricardo Matias 1,2 1
Universidade de Lisboa, Faculdade de Motricidade Humana, Neuromechanics Research Group – Interdisciplinary Centre for the Study of Human Performance (CIPER), LBMF, Estrada da Costa, 1499-002 Cruz Queb, Lisbon, Portugal 2 Escola Superior de Sau´de, Instituto Polite´cnico de Setu´bal, Campus do Instituto Polite´cnico de Setu´bal, Estefanilha, Edifı´cio ESCE, 2914-503 Setu´bal, Portugal
Introduction: Osteoarthritis is an insidious disease that affects patients gait functionality with great expression in the ability to perform daily living activities decreasing their quality of life [1]. Early diagnosis is one of the most important factors for a favourable prognosis. Research on gait analysis in individuals with osteoarthritis points to spatiotemporal parameters, as the ones with the most significant correlation to the disease progression [2]. These parameters are normally assessed in specialised biomechanical laboratories equipped with state-of-the-art systems and highly skilled human resources. With today’s unprecedented technological evolution in sensor’s miniaturisation and computational performance, a huge opportunity arises to run a complete gait analysis, anywhere and reach a broader population. Research question: Can an ambulatory inertial measurement system detect spatial and temporal minor gait induced asymmetries in healthy subjects? Methods: A sample of 17 healthy participants (22.76 5.66 years) was recruited by means of geographic convenience. All participants were submitted to a gait asymmetry protocol in a two belt Bertec Fully Instrumented Treadmill while 3D kinematics was recorded with 17 inertial measurement units (XSens MVNBiomech) with a sample of 120 Hz in a full body configuration. After walking 30 s with both belts at 1 m/s (the average gait speed in older adults [3]) a gait protocol of 24 levels was randomly assigned to one of the belts with a speed decrease of 0.01 m/s at each 10 s. The protocol ended with a speed asymmetry of 0.24 m/s between treadmill’s belts, corresponding to the average gait
* Corresponding author. E-mail address: [email protected] (R. Martins). http://dx.doi.org/10.1016/j.gaitpost.2016.07.151 0966-6362/
asymmetry observed in individuals with an early diagnosis of osteoarthritis [1]. An automated pipeline was developed in Python to process and statistically analyse the data. Gait spatiotemporal parameters (cadence, stance time and swing time) were computed for both lower limbs and an intra-subject comparison performed in each protocol speed level. Results: The results of the Mann–Whitney U test revealed that the spatiotemporal parameter swing time showed statistically significant differences between the two lower limbs at the level 21 (p = 0.05), level 22 (p = 0.045), level 23 (p = 0.011), level 24 (p = 0.015) and level 25 (p = 0.033). Discussion: This study results show that by merging an ambulatory kinematic system with automated data analysis it is possible to detect minor gait spatiotemporal asymmetries. The asymmetry magnitude at which the statistical differences were found to be significant, was inferior to the magnitude described in patients with an early diagnosis of osteoarthritis. Further work is required but such a solution holds a great promise to evolve into a new movement disorder screening metric that can be implemented in the most widely used equipment with inertial sensors – the smartphone.
References [1] Jayalath. Int. J. Physiother. Res. 2014;2:677–80. [2] Constantinou. J. Orthop. Sports Phys. Ther. 2014;44. [3] Hollman. Gait Posture 2011;34:111–8.