Yıl: 2021 Cilt: 11 Sayı: 2 Sayfa Aralığı: 149 - 156 Metin Dili: İngilizce DOI: 10.4274/jarem.galenos.2021.3980 İndeks Tarihi: 22-11-2021

A New Algorithm for Dynamic Vestibular System Analysis with Wearable Pressure and Motion Sensors

Öz:
Objective: Balance is a complex state that requires integrating information from many systems into various levels of the nervous system and the actions of commands from the central nervous system and the musculoskeletal system. Postural control is the ability to maintain body position against forces that threaten the individual’s orientation or balance. In our study, a mobile prototype system was used to create equilibrium data of subjects and generate a set of normal values, diseases and fuzzy decisions. Methods: This study included 106 adults (55 females, 51 males) with no vestibular, neurologic, orthopaedic and eye problems to create the normalisation data. Also, 60 patients (37 females, 23 males) with different vestibular pathologies (23 benign paroxysmal positional vertigo, 12 Meniere’s disease, 10 vestibular neuritis, 15 unilateral vestibular hypofunction) comprised the patient group. Results: With the newly developed system, step length and symmetry, distance between feet, gait symmetry, ankle mobility and symmetry and phases of each step and step symmetry were collected. Significant differences were found between the normal and pathological groups in the data obtained from the dynamic balance and pressure sensors on the sole of the foot. Conclusion: Dynamic balance and walking analysis by our system are considered important in audiology, orthopaedics and neurology. It can contribute clinically by collecting data from several patients with different pathologies.
Anahtar Kelime:

Giyilebilir Basınç ve Hareket Sensörleri ile Dinamik Vestibüler Sistem Analiz Algoritması Geliştirilmesi

Öz:
Amaç: Denge, merkezi sinir sistemi ve kas-iskelet sistemi komutlarının eylemlerini içine alan, birçok sistemden bilgi entegrasyonunu gerektiren karmaşık bir yapıdır. Postüral kontrol, bireyin yönelimini veya dengesini tehdit eden kuvvetlere karşı vücut pozisyonunu sürdürme yeteneğidir. Çalışmamızda, deneklerin denge verilerini oluşturmak için; bir dizi normal birey değeri, hastalıklar için, farklı hastalık gruplarından veriler toplanarak, bulanık kararlar oluşturmak amacıyla mobil prototip sistem kullanılmıştır. Yöntemler: Normalizasyon verileri oluşturmak için vestibüler, nörolojik, ortopedik ve göz problemi olmayan 106 yetişkin (55 kadın, 51 erkek) ve farklı vestibüler patolojileri olan 60 hasta (37 kadın, 23 erkek) (23 benign paroksismal pozisyonel vertigo, 12 Meniere hastalığı, 10 vestibüler nörit, 15 tek taraflı vestibüler hipofonksiyon) hasta grubunu oluşturmuştur. Bulgular: Yeni geliştirilen sistem, adım uzunluğu ve simetrisi ile ayaklar arası mesafe, yürüyüş simetrisi, ayak bileği hareketliliği ve simetrisi, adım simetrisi ve adım simetrisinin faz bilgileri toplanmıştır. Ayak tabanındaki basınç sensörleri ve vücutta yer alan hareket sensörleri ile elde edilen dinamik denge değerlerinde, normal ve patolojik gruplar arasında önemli farklılıklar bulunmuştur. Sonuç: Sistemimiz tarafından yapılan dinamik denge ve yürüme analizinin; odyoloji, ortopedi, nöroloji alanlarındaki hastaları tanı ve takipte önemli olduğu düşünülmektedir. Farklı patolojilere sahip bir dizi hastadan veri toplayarak, klinik olarak farklı hastalıkların tanısı ve takibinde katkı sağlayacağı düşünülmektedir.
Anahtar Kelime:

Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
  • 1. Ferrè ER, Bottini G, Iannetti GD, Haggard P. The balance of feelings: vestibular modulation of bodily sensations. Cortex 2013; 49: 748-58.
  • 2. Palm HG, Lang P, Strobel J, Riesner HJ, Friemert B. Computerized dynamic posturography. Am J Phys Med Rehabil [Internet] 2014; 93: 49- 55.
  • 3. Nesti A, Barnett-Cowan M, Macneilage PR, Bülthoff HH. Human sensitivity to vertical self-motion. Exp Brain Res 2014; 232: 303-14.
  • 4. Şimşek D, Ertan H. Control and sport : muscular fatıgue and postural control relationship. Spormetre Beden Eğitimi ve Spor Bilim Derg 2011; 9: 119-24.
  • 5. Bertolini G, Straumann D. Moving in a Moving World: A Review on Vestibular Motion Sickness. Front Neurol 2016; 15; 7:14.
  • 6. Mast FW, Preuss N, Hartmann M, Grabherr L. Spatial cognition, body representation and affective processes: the role of vestibular information beyond ocular reflexes and control of posture. Front Integr Neurosci 2014; 8: 44. doi: 10.3389/fneur.2016.00014.
  • 7. Hegde N, Bries M, Sazonov E. A Comparative Review of Footwear- Based Wearable Systems. Electronics. 2016; 5. https://doi.org/10.3390/ electronics5030048 [E-pub online ahead]
  • 8. Roetenberg D, Luinge H, Slycke P. Xsens MVN : Full 6DOF Human Motion Tracking Using Miniature Inertial Sensors. Technical report. 2013. Available from: http://en.souvr.com/product/pdf/MVN_white_paper.pdf 9. Dye DC, Eakman AM, Bolton KM. Assessing the validity of the dynamic gait index in a balance disorders clinic: an application of Rasch analysis. Phys Ther 2013; 93: 809-18.
  • 10. Bent LR, Inglis JT, McFadyen BJ. When is vestibular information important during walking? J Neurophysiol 2004; 92: 1269-75.
  • 11. Shull PB, Jirattigalachote W, Hunt MA, Cutkosky MR, Delp SL. Quantified self and human movement: a review on the clinical impact of wearable sensing and feedback for gait analysis and intervention. Gait Posture 2014; 40: 11-9.
  • 12. Jarchi D, Wong C, Kwasnicki RM, Heller B, Tew GA, Yang GZ. Gait parameter estimation from a miniaturized ear-worn sensor using singular spectrum analysis and longest common subsequence. IEEE Trans Biomed Eng 2014; 61: 1261-73.
  • 13. Howell AM, Kobayashi T, Hayes HA, Foreman KB, Bamberg SJ. Kinetic gait analysis using a low-cost ınsole. IEEE Trans Biomed Eng 2013; 60: 3284-90.
  • 14. Mariani B, Rouhani H, Crevoisier X, Aminian K. Quantitative estimation of foot-flat and stance phase of gait using foot-worn inertial sensors. Gait Posture 2013; 37: 229-34.
  • 15. Riaz Q, Tao G, Krüger B, Weber A. Motion reconstruction using very few accelerometers and ground contacts. Graphical Models 2015; 79: 23-38.
  • 16. Khandelwal S, Wickstrom N. Gait event detection in real-world environment for long-term applications: ıncorporating domain knowledge ınto time-frequency analysis. IEEE Trans Neural Syst Rehabil Eng 2016; 24: 1363-72.
  • 17. Angunsri N, Ishikawa K, Yin M, Omi E, Shibata Y, Saito T, et al. Gait instability caused by vestibular disorders - analysis by tactile sensor. Auris Nasus Larynx 2011; 38: 462-8.
  • 18. Borel L, Harlay F, Lopez C, Magnan J, Chays A, Lacour M. Walking performance of vestibular-defective patients before and after unilateral vestibular neurotomy. Behav Brain Res 2004; 150: 191-200.
  • 19. Demain A, Westby GW, Fernandez-Vidal S, Karachi C, Bonneville F, Do MC, et al. High-level gait and balance disorders in the elderly: a midbrain disease? J Neurol 2014; 261: 196-206.
  • 20. Kubo T, Kumakura H, Hirokawa Y, Yamamoto K, Imai T, Hirasaki E. 3D analysis of human locomotion before and after caloric stimulation. Acta Otolaryngol. 1997; 117: 143-8.
  • 21. Horak FB, Dozza M, Peterka R, Chiari L, Wall C 3rd. Vibrotactile biofeedback improves tandem gait in patients with unilateral vestibular loss. Ann N Y Acad Sci 2009; 1164: 279-81.
  • 22. Barker SP. Changes in gait, balance, and function with vestibular rehabilitation [Internet]. Vol. 3126514, ProQuest Dissertations and Theses. 2004. Available from: http://search.proquest.com/do cview/305179306?accountid=14701%5Cnhttp://sfx.scholarsportal.info/ ottawa?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:diss ertation&genre=dissertations+%26+theses&sid=ProQ:ProQuest+D issertat ions+%26+Theses+Global& atitle
  • 23. Alberts JL, Hirsch JR, Koop MM, Schindler DD, Kana DE, Linder SM, et al. Using Accelerometer and Gyroscopic Measures to Quantify Postural Stability. J Athl Train 2015; 50: 578-88.
  • 24. O’Sullivan M, Blake C, Cunningham C, Boyle G, Finucane C. Correlation of accelerometry with clinical balance tests in older fallers and nonfallers. Age Ageing 2009; 38: 308-13.
  • 25. Crea S, Donati M, De Rossi SM, Oddo CM, Vitiello N. A wireless flexible sensorized insole for gait analysis. Sensors (Basel) 2014; 14: 1073-93.
  • 26. Bohannon RW, Horton MG, Wikholm JB. Importance of four variables of walking to patients with stroke. Int J Rehabil Res 1991; 14: 246-50.
  • 27. Lang J, Ishikawa K, Hatakeyama K, Wong WH, Yin M, Saito T, et al. 3D body segment oscillation and gait analysis for vestibular disorders. Auris Nasus Larynx 2013; 40: 18-24.
  • 28. Liu T, Inoue Y, Shibata K. Development of a wearable sensor system for quantitative gait analysis. Meas J Int Meas Confed 2009; 42: 978-88.
  • 29. Hung TN, Suh YS. Inertial sensor-based two feet motion tracking for gait analysis. Sensors (Basel) 2013; 13: 5614-29.
APA KARA E, IKIZOGLU S, ŞAHİN K, Cakar T, Atas A (2021). A New Algorithm for Dynamic Vestibular System Analysis with Wearable Pressure and Motion Sensors. , 149 - 156. 10.4274/jarem.galenos.2021.3980
Chicago KARA Eyyup,IKIZOGLU SERHAT,ŞAHİN Kaan,Cakar Tunay,Atas Ahmet A New Algorithm for Dynamic Vestibular System Analysis with Wearable Pressure and Motion Sensors. (2021): 149 - 156. 10.4274/jarem.galenos.2021.3980
MLA KARA Eyyup,IKIZOGLU SERHAT,ŞAHİN Kaan,Cakar Tunay,Atas Ahmet A New Algorithm for Dynamic Vestibular System Analysis with Wearable Pressure and Motion Sensors. , 2021, ss.149 - 156. 10.4274/jarem.galenos.2021.3980
AMA KARA E,IKIZOGLU S,ŞAHİN K,Cakar T,Atas A A New Algorithm for Dynamic Vestibular System Analysis with Wearable Pressure and Motion Sensors. . 2021; 149 - 156. 10.4274/jarem.galenos.2021.3980
Vancouver KARA E,IKIZOGLU S,ŞAHİN K,Cakar T,Atas A A New Algorithm for Dynamic Vestibular System Analysis with Wearable Pressure and Motion Sensors. . 2021; 149 - 156. 10.4274/jarem.galenos.2021.3980
IEEE KARA E,IKIZOGLU S,ŞAHİN K,Cakar T,Atas A "A New Algorithm for Dynamic Vestibular System Analysis with Wearable Pressure and Motion Sensors." , ss.149 - 156, 2021. 10.4274/jarem.galenos.2021.3980
ISNAD KARA, Eyyup vd. "A New Algorithm for Dynamic Vestibular System Analysis with Wearable Pressure and Motion Sensors". (2021), 149-156. https://doi.org/10.4274/jarem.galenos.2021.3980
APA KARA E, IKIZOGLU S, ŞAHİN K, Cakar T, Atas A (2021). A New Algorithm for Dynamic Vestibular System Analysis with Wearable Pressure and Motion Sensors. JAREM, 11(2), 149 - 156. 10.4274/jarem.galenos.2021.3980
Chicago KARA Eyyup,IKIZOGLU SERHAT,ŞAHİN Kaan,Cakar Tunay,Atas Ahmet A New Algorithm for Dynamic Vestibular System Analysis with Wearable Pressure and Motion Sensors. JAREM 11, no.2 (2021): 149 - 156. 10.4274/jarem.galenos.2021.3980
MLA KARA Eyyup,IKIZOGLU SERHAT,ŞAHİN Kaan,Cakar Tunay,Atas Ahmet A New Algorithm for Dynamic Vestibular System Analysis with Wearable Pressure and Motion Sensors. JAREM, vol.11, no.2, 2021, ss.149 - 156. 10.4274/jarem.galenos.2021.3980
AMA KARA E,IKIZOGLU S,ŞAHİN K,Cakar T,Atas A A New Algorithm for Dynamic Vestibular System Analysis with Wearable Pressure and Motion Sensors. JAREM. 2021; 11(2): 149 - 156. 10.4274/jarem.galenos.2021.3980
Vancouver KARA E,IKIZOGLU S,ŞAHİN K,Cakar T,Atas A A New Algorithm for Dynamic Vestibular System Analysis with Wearable Pressure and Motion Sensors. JAREM. 2021; 11(2): 149 - 156. 10.4274/jarem.galenos.2021.3980
IEEE KARA E,IKIZOGLU S,ŞAHİN K,Cakar T,Atas A "A New Algorithm for Dynamic Vestibular System Analysis with Wearable Pressure and Motion Sensors." JAREM, 11, ss.149 - 156, 2021. 10.4274/jarem.galenos.2021.3980
ISNAD KARA, Eyyup vd. "A New Algorithm for Dynamic Vestibular System Analysis with Wearable Pressure and Motion Sensors". JAREM 11/2 (2021), 149-156. https://doi.org/10.4274/jarem.galenos.2021.3980