Application of the Chaos Theory in the Analysis of EMG on Patients with Facial Paralysis

Xiong, Anbin; Zhao, Xingang; Han, Jianda; Liu, Guangjun

doi:10.1007/978-3-319-05582-4_71

Cited by 10 publications

(4 citation statements)

References 28 publications

(35 reference statements)

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“…Numerous national and international studies have been conducted on chaos and chaotic systems in recent years. Control [2], biomedical [3,4], secure communication [5,6], image processing [7,8], fuzzy logic [9], artificial neural networks [10,11], random number generators [12,13], industrial control [14,15], secure communication [16] and cryptography [17] can be given as examples of these studies.…”

Section: Introductionmentioning

confidence: 99%

A Novel Dormand-Prince Based Hybrid Chaotic True Random Number Generator on FPGA

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et al. 2021

Balkan Journal of Electrical and Computer Engineering

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This study presents a Dormand-Prince-based hybrid chaotic True Random Number Generator Design (TRNG) that can be used for secure communication and cryptographic applications on Field Programmable Gate Array (FPGA). In this design, a chaotic oscillator unit has been implemented with an FPGA-based Sprott-Jafari chaotic oscillator model suitable with IQ-Math fixed point number and IEEE 754-1985 floating point number standards. Random numbers have been produced with the quantization of the results generated by the chaotic oscillator. XOR has been performed with FPGA-based ring oscillator structure on the post-processing unit so as to enhance the randomness. The differential equation of the chaotic system used in the TRNG design was modelled using Dormand-Prince numerical algorithm method. The design on FPGA has been realized in two separate number formats including 32-bit (16I-16Q) IQ-Math fixed point number standard and 32-bit IEEE 754-1985 floating point number standard. The realized design has been coded in VHDL, a hardware description language, and the Xilinx ISE 14.7 program has been used for the system design. The TRNG design has been synthesized and tested for the Virtex-6 (XC6VLX240T-1FF1156) FPGA chip. The maximum operating frequencies of the TRNG in 32-bit IQ-Math fixed point number standard and 32-bit IEEE 754-1985 floating point number standard reach 344.585 MHz and 316 MHz, respectively. The throughputs of the TRNG in 32-bit IQ-Math fixed point number standard and 32-bit IEEE 754-1985 floating point number standard have been obtained as 344 Mbit/s and 316 Mbit/s, respectively. 1 Mbit sequence has been generated by using TRNG system. Randomness analysis of the generated numbers has been

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Section: Introductionmentioning

confidence: 99%

A Novel Dormand-Prince Based Hybrid Chaotic True Random Number Generator on FPGA

Koyuncu

Şeker²,

Alçın

et al. 2021

Balkan Journal of Electrical and Computer Engineering

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“…Hayashi [12] related the delayed coordinates map to changes provoked by anesthesia in the electroencephalograph (EEG). Xiong et al [13] explored the ability of Poincaré plots from electromyogram (EMG) to reflect facial paralysis and Son et al [14] studied regularity in respiratory signals using this same technique.…”

Section: Introductionmentioning

confidence: 99%

Poincaré plot analysis of cerebral blood flow signals: Feature extraction and classification methods for apnea detection

et al. 2018

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ObjectiveRheoencephalography is a simple and inexpensive technique for cerebral blood flow assessment, however, it is not used in clinical practice since its correlation to clinical conditions has not yet been extensively proved. The present study investigates the ability of Poincaré Plot descriptors from rheoencephalography signals to detect apneas in volunteers.MethodsA group of 16 subjects participated in the study. Rheoencephalography data from baseline and apnea periods were recorded and Poincaré Plot descriptors were extracted from the reconstructed attractors with different time lags (τ). Among the set of extracted features, those presenting significant differences between baseline and apnea recordings were used as inputs to four different classifiers to optimize the apnea detection.ResultsThree features showed significant differences between apnea and baseline signals: the Poincaré Plot ratio (SDratio), its correlation (R) and the Complex Correlation Measure (CCM). Those differences were optimized for time lags smaller than those recommended in previous works for other biomedical signals, all of them being lower than the threshold established by the position of the inflection point in the CCM curves. The classifier showing the best performance was the classification tree, with 81% accuracy and an area under the curve of the receiver operating characteristic of 0.927. This performance was obtained using a single input parameter, either SDratio or R.ConclusionsPoincaré Plot features extracted from the attractors of rheoencephalographic signals were able to track cerebral blood flow changes provoked by breath holding. Even though further validation with independent datasets is needed, those results suggest that nonlinear analysis of rheoencephalography might be a useful approach to assess the correlation of cerebral impedance with clinical changes.

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“…Mühendisliğin pek çok alanında kaotik sistemlerin varlığının ortaya çıkarılması, bu konuda yapılan yoğun çalışmalar ve yaşanan gelişmeler kaotik sistemlerin birçok uygulama alanında kullanılabileceğini göstermiştir. Bu uygulama alanlarına kriptografi, güvenli haberleşme, biyomedikal, kuantum elektroniği, görüntü işleme, optik elektronik, kontrol, optimizasyon, yapay sinir ağları gibi alanlar örnek olarak verilebilir [2][3][4]. Kaotik işaretlerin elektronik mühendisliğindeki önemli araştırma ve uygulama alanları arasında güvenli haberleşme düzenekleri oluşturma, şifreleme, gürültü üreteçleri, ikili-kodlu rasgele sayı üreteçleri bulunmaktadır.…”

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Real time implementation of a novel chaotic generator on FPGA

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et al. 2015

2015 23nd Signal Processing and Communications Applications Conference (SIU)

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Özetçe-Buçalışmada, literatüre sürekli zamanlı yeni bir otonom kaotik sistem sunulmuş ve FPGA üzerinde sayısal olarak gerçeklenmiştir. Sunulan yeni kaotik sistem, FPGA üzerinde IEEE 754-1985 kayan noktalı sayı formatında, Heun algoritması kullanılarak VHDL dili ile gerçekleştirilmiştir. Tasarlanan sistem Xilinx Virtex-6 FPGA çipinde sentezlenmiş ve test edilmiştir. Test sonuçlarına göre FPGA-tabanlı yeni kaotik işaret üretecinin çalışma frekansı 390 MHz olarak belirlenmiş ve çip istatistikleri ile performans sonuçları verilmiştir. Ayrıca, FPGA-tabanlı yeni kaotik işaret üretecinden elde edilen sonuçlar ile Matlab-tabanlı nümerik sonuçlar karşılaştırılmış ve başarılı sonuçlar elde edildiği görülmüştür. Geliştirilen FPGA tabanlı kaotik sistem modeli kullanılarak, rasgele sayı üretimi ve güvenli haberleşme gibi kaos tabanlı çeşitli mühendislik uygulamaları gerçekleştirilebilir. Anahtar Kelimeler-Kaos; Kaotik sistemler; Heun; FPGA; VHDL.Abstract-In this study, a new continuous-time autonomous chaotic system has been presented and implemented on FPGA. Presented a new chaotic system has been designed using the IEEE 754-1985 floating-point format and implemented using Heun algorithm with VHDL language. The designed system has been synthesized and tested on Xilinx Virtex-6 FPGA chip. According to the test results, operation frequency of the FPGA-based a new chaotic signal generator is certain as 390 MHz and performance results have been given with chip statistics. In addition, the results obtained from FPGA-based new chaotic generator have been compared with the Matlab-based numerical results and it has been observed that obtained results are successful. By the developed FPGA-based novel chaotic system model, chaos-based various engineering applications such as true random number generation and secure communication system can be performed.

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Application of the Chaos Theory in the Analysis of EMG on Patients with Facial Paralysis

Cited by 10 publications

References 28 publications

A Novel Dormand-Prince Based Hybrid Chaotic True Random Number Generator on FPGA

A Novel Dormand-Prince Based Hybrid Chaotic True Random Number Generator on FPGA

Poincaré plot analysis of cerebral blood flow signals: Feature extraction and classification methods for apnea detection

Real time implementation of a novel chaotic generator on FPGA

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