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نتیجه جستجو - تشخیص وضعیت

تعداد مقالات یافته شده: 3
ردیف عنوان نوع
1 A new method of diagnosing athletes anterior cruciate ligament health status using surface electromyography and deep convolutional neural network
یک روش جدید برای تشخیص وضعیت سلامت رباط صلیبی خلفی ورزشکاران با استفاده از الکترومیوگرافی سطح و شبکه عصبی کانونال عمقی-2019
Anterior cruciate ligament (ACL) injury is one of the most common injuries in high-demand sports. Due to long-term treatment of this injury, diagnosing recovery of ACL becomes important, particularly six months postoperatively. The purpose of this research is to provide a cost-effective and intelligent method to diagnose ACLs health status. For this purpose, 11 healthy and 27 ACL-injured subjects have been selected. In the proposed method, the athlete performs a single-leg landing protocol and surface electromyographic signals (EMG) are taken from eight lower limb muscles. Then, time–frequency distributions of EMG signals in each landing are calculated as an image, using pseudo Wigner–Ville distribution (PWVD), which are the inputs of a deep convolutional neural network (DCNN). By time–frequency analysis, it has been made clear that any change in ACLs health status causes changes in the extent of energy spread in PWVD, distribution volume, frequency content, damping rate and the peak value of EMG signals. In this research, a new relationship between ACLs health status and lower limb muscles activity is introduced through moni- toring of PWVD images. The result indicates that the designed expert system is able to diagnose ACLs health status with 95.8% accuracy. In this non-invasive method, PWVD images of EMG signals are chosen as the inputs of DCNN, instead of MRI images, which, in addition to their high accuracy in diagnosing, are safer and much cheaper. The presented method can play an important role in assessing the recovery process, six months postoperatively and after that.
Keywords: ACLs health status | Single-leg landing | Surface electromyography | Pseudo Wigner–Ville distribution | Deep convolutional neural networks
مقاله انگلیسی
2 A mobile application to report and detect 3D body emotional poses
یک برنامه کاربردی تلفن همراه برای گزارش و کشف نکات سه بعدی عاطفی بدن-2019
Most research into automatic emotion recognition is focused on facial expressions or physiological signals, while the exploitation of body postures has scarcely been explored, although they can be useful for emo- tion detection. This paper first explores a mechanism for self-reporting body postures with a novel easy- to-use mobile application called EmoPose. The app detects emotional states from self-reported poses, classifying them into the six basic emotions proposed by Ekman and a neutral state. The poses identi- fied by Schindler et al. have been used as a reference and the nearest neighbor algorithm used for the classification of poses. Finally, the accuracy in detecting emotions has been assessed by means of poses reported by a sample of users.
Keywords: Affective com puting | App | Emotion detection | Mobile application | Pose detection | Expert system
مقاله انگلیسی
3 مقدمه ای بر منطق فازی
سال انتشار: 2013 - تعداد صفحات فایل pdf انگلیسی: 24 - تعداد صفحات فایل doc فارسی: 28
منطق فازی، توسعه منطق بولی توسط لطفی زاده در سال 1965 براساس تئوری ریاضی مجموعه های فازی است که تعمیمی از تئوری مجموعه کلاسیک است. با معرفی مفهوم درجه در تشخیص وضعیت (و از اینرو سبب می شود تا وضعیتی بیش از دو حالت صحیح و غلط، موجود باشد) منطق فازی، انعطاف پذیری بسیار ارزشمندی را برای استدلال فراهم می سازد و بوسیله ان محاسبه خطاها و عدم اطمینان، ممکن می شود.
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