Prediction of Muscle Fatigue during Minimally Invasive Surgery Using Recurrence Quantification Analysis
المؤلفون المشاركون
Keshavarz Panahi, Ali
Cho, Sohyung
المصدر
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2016)، ص ص. 1-8، 8ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2016-05-24
دولة النشر
مصر
عدد الصفحات
8
التخصصات الرئيسية
الملخص EN
Due to its inherent complexity such as limited work volume and degree of freedom, minimally invasive surgery (MIS) is ergonomically challenging to surgeons compared to traditional open surgery.
Specifically, MIS can expose performing surgeons to excessive ergonomic risks including muscle fatigue that may lead to critical errors in surgical procedures.
Therefore, detecting the vulnerable muscles and time-to-fatigue during MIS is of great importance in order to prevent these errors.
The main goal of this study is to propose and test a novel measure that can be efficiently used to detect muscle fatigue.
In this study, surface electromyography was used to record muscle activations of five subjects while they performed fifteen various laparoscopic operations.
The muscle activation data was then reconstructed using recurrence quantification analysis (RQA) to detect possible signs of muscle fatigue on eight muscle groups (bicep, triceps, deltoid, and trapezius).
The results showed that RQA detects the fatigue sign on bilateral trapezius at 47.5 minutes (average) and bilateral deltoid at 57.5 minutes after the start of operations.
No sign of fatigue was detected for bicep and triceps muscles of any subject.
According to the results, the proposed novel measure can be efficiently used to detect muscle fatigue and eventually improve the quality of MIS procedures with reducing errors that may result from overlooked muscle fatigue.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Keshavarz Panahi, Ali& Cho, Sohyung. 2016. Prediction of Muscle Fatigue during Minimally Invasive Surgery Using Recurrence Quantification Analysis. Minimally Invasive Surgery،Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1111349
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Keshavarz Panahi, Ali& Cho, Sohyung. Prediction of Muscle Fatigue during Minimally Invasive Surgery Using Recurrence Quantification Analysis. Minimally Invasive Surgery No. 2016 (2016), pp.1-8.
https://search.emarefa.net/detail/BIM-1111349
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Keshavarz Panahi, Ali& Cho, Sohyung. Prediction of Muscle Fatigue during Minimally Invasive Surgery Using Recurrence Quantification Analysis. Minimally Invasive Surgery. 2016. Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1111349
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1111349
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر