Kombinacija vremensko-frekvencijske analize signala i strojnoga učenja uz primjer u detekciji gravitacijskih valova

This paper presents a method for classifying noisy, non-stationary signals in the time-frequency domain using artificial intelligence. The preprocessed time-series signals are transformed into time-frequency representations (TFrs) from Cohen’s class resulting in the TFr images, which are used as input to the machine learning algorithms. We have used three state-of-the-art deep-learning 2d convolutional neural network (Cnn) architectures (ResNet-101, Xception, and EfficientNet). The method was demonstrated on the challenging task of detecting gravitational-wave (gw) signals in intensive real-life, non-stationary, non-gaussian, and non-white noise. The results show excellent classification performance of the proposed approach in terms of classification accuracy, area under the receiver operating characteristic curve (roC auC), recall, precision, F1 score, and area under the precision-recall curve (PR AUC). The novel method outperforms the baseline machine learning model trained on the time-series data in terms of all considered metrics. The study indicates that the proposed technique can also be extended to various other applications dealing with non-stationary data in intensive noise.Ovaj rad predstavlja metodu klasifikacije šumom narušenih nestacionarnih signala u vremensko-frekvencijskoj domeni korištenjem umjetne inteligencije. Naime, signali u obliku vremenskih nizova transformirani su nakon predobrade u vremensko-frekvencijske prikaze (TFR) iz Cohenove klase, rezultirajući TFR slikama korištenim kao ulaz u algoritme strojnoga učenja. Korištene su tri suvremene metode dubokoga učenja u obliku 2D arhitektura konvolucijskih neuronskih mreža (CNN) (ResNet-101, Xception i EfficientNet). Metoda je demonstrirana na zahtjevnom problemu detekcije signala gravitacijskih valova (GW) u intenzivnom stvarnom i nestacionarnom šumu koji nema karakteristike ni Gaussovog ni bijelog šuma. Rezultati pokazuju izvrsne performanse klasifikacije predloženoga pristupa s obzirom na točnost klasifikacije, površinu ispod krivulje značajke djelovanja prijamnika (ROC AUC), odziv, preciznost, F1-mjeru i površinu ispod krivulje preciznost-odziv (PR AUC). Nova metoda nadmašuje osnovni model strojnoga učenja treniran na podatcima u obliku vremenskih nizova s obzirom na razmatrane metrike. Istraživanje pokazuje da se predložena tehnika može proširiti i na različite druge primjene koje uključuju nestacionarne podatke u intenzivnom šumu

EMG KONTROLA ROBOTSKE RUKE

U ovom radu istražujemo nastanak EMG signala u tijelu čovjeka te osnovne mehanizme iza njegovog stvaranja, te definiramo moguće načine akvizicije EMG signala iz mišića, nadalje opisujemo karakteristike EMG signala. Prikazujemo već ostvarene sustave za upravljanje robotskom rukom pomoću EMG signala te prikazujemo njihove mogućnosti za upravljanje jednim takvim sustavom, deklariramo ih s obzirom na koliko mišića snimaju EMG signal i s obzirom na način obrade toga signala. Nakon toga predlažemo idejno rješenje jednog EMG sustava za kontrolu robotskom rukom, te prolazimo kroz sastavne dijelove objašnjavajući princip rada svakog, prikazujemo utjecaj na signal i određujemo vrijednosti potrebnih komponenata. Pomoću tih saznanja određujemo završnu shemu pomoću koje dizajniramo i izrađujemo tiskanu pločicu na koju onda postavljamo komponente, te prikazujemo način spajanja na EMG pločice na mikrokontroler.This paper researches the generation of EMG signals in the human body and the basic mechanisms behind its creation, defining the possible ways of acquisition of EMG signals from muscles and further describing the characteristics of the EMG signal. We present already realized control systems for a robotic arm using EMG signals and show their way of controlling a robotic arm, we declare them with a regard to how many muscles do we record the EMG signal from and with respect to the method of processing that signal. After that, we propose a conceptual design of a system for EMG control of a robotic arm, and go through the parts of the system explaining the principle of operation of each, show the influence of the signal and determine the value of the necessary components. We use these insights determine the final schematic with help of which we design and build a printed circuit board and we populate it with components, and then we show how to connect the microcontroller to the EMG board

EMG KONTROLA ROBOTSKE RUKE

U ovom radu istražujemo nastanak EMG signala u tijelu čovjeka te osnovne mehanizme iza njegovog stvaranja, te definiramo moguće načine akvizicije EMG signala iz mišića, nadalje opisujemo karakteristike EMG signala. Prikazujemo već ostvarene sustave za upravljanje robotskom rukom pomoću EMG signala te prikazujemo njihove mogućnosti za upravljanje jednim takvim sustavom, deklariramo ih s obzirom na koliko mišića snimaju EMG signal i s obzirom na način obrade toga signala. Nakon toga predlažemo idejno rješenje jednog EMG sustava za kontrolu robotskom rukom, te prolazimo kroz sastavne dijelove objašnjavajući princip rada svakog, prikazujemo utjecaj na signal i određujemo vrijednosti potrebnih komponenata. Pomoću tih saznanja određujemo završnu shemu pomoću koje dizajniramo i izrađujemo tiskanu pločicu na koju onda postavljamo komponente, te prikazujemo način spajanja na EMG pločice na mikrokontroler.This paper researches the generation of EMG signals in the human body and the basic mechanisms behind its creation, defining the possible ways of acquisition of EMG signals from muscles and further describing the characteristics of the EMG signal. We present already realized control systems for a robotic arm using EMG signals and show their way of controlling a robotic arm, we declare them with a regard to how many muscles do we record the EMG signal from and with respect to the method of processing that signal. After that, we propose a conceptual design of a system for EMG control of a robotic arm, and go through the parts of the system explaining the principle of operation of each, show the influence of the signal and determine the value of the necessary components. We use these insights determine the final schematic with help of which we design and build a printed circuit board and we populate it with components, and then we show how to connect the microcontroller to the EMG board

Realization of device for IR head stimulation

U ovom radu opisan proces apsorpcije valnih duljina svijetlosti u fotoakceptorima na kojemu se temelji fotobiomodulacija, nabrojane su primjene fotobiomodulacije u medicini općenito, te su objašnjeni načini, istraživanja i moguće primjene fotobiomodulacije mozga. Nadalje, prikazan je komercijalan uređaj za fotobiomodulaciju mozga, te su objašnjeni pojedini parametri koji su krucijalni pri izvođenju pravilnog tretmana fotobiomodulacije. Nakon toga je napravljen dizajn kod kojega su proračunate i odabrane vrijednosti potrebnih elemenata, te je realiziran sklop za generiranje pravokutnog valnog oblika radnog ciklusa od 50% s mogućim odabirom između tri frekvencije modulacije napona i struje napajanja blisko infracrvenih svijetlećih dioda. Realizirani su LED klasteri spajanjem svijetlećih dioda u seriju radi smanjivanja gubitaka i uklanjanja potrebe za prilagodbu napona napajanja, koji su onda spojeni paralelno. Svi su moduli montirani na kacigu „Ultracortex IV“ kao nosivu strukturu, klasteri su pozicionirani na potrebna mjesta iznad željenih dijelova mozga koji se žele stimulirati, a napajanje je realizirano prijenosnim USB napajanjem radi jednostavnosti i lakšeg korištenja. Potom su izvedena mjerenja na dvije osobe pri dva različita stanja mozga, opušteno stanje pri kojem se koristila foto stimulacija od 10 Hz i koncentrirano stanje pri kojem se koristila foto stimulacija od 20 Hz, pri čemu se je mjerio EEG signal mozga prije i tijekom foto stimulacije mozga. Nakon toga su izmjereni EEG signali obrađeni na način da se dobije spektri frekvencija prije i tijekom foto stimulacije čijom usporedbom se došlo do zaključka ukoliko fotobiomodulacija radi smetnje mjerenju EEG signala te ukoliko postoji utjecaj na rad mozga odnosno na spektar EEG signala. Pri čemu se smatra da fotobiomodulacija nije radila smetnje na EEG te je kod jednog ispitanika zapažena značajan utjecaj fotobiomodulacije na spektar EEG signala.This paper describes the process of absorption of wavelengths of light in photo acceptors, on which photo biomodulation is based, lists the applications of photo biomodulation in medicine in general, and explains the methods, studies and possible applications of brain photo biomodulation. Furthermore, a commercial device for brain photo biomodulation is shown, and some parameters that are crucial in performing the proper photo biomodulation treatment are explained. After that, a circuit was designed and the values of the required elements were calculated and selected, circuit for generating a rectangular duty cycle waveform of 50% was realized, with a possible choice between three frequencies of modulating the supply voltage and current for the near-infrared LED-s. LED clusters were implemented by connecting LED-s in series to reduce losses and eliminate the need to adjust the supply voltage, which were then connected in parallel. All modules were mounted on the "Ultracortex IV" helmet as a load-bearing structure, the clusters are positioned in the necessary places above the desired parts of the brain to be stimulated, and the power is provided by using portable USB power because of its simplicity and ease of use. Measurements were made on two persons and were performed with two different brain states, a relaxed condition using 10 Hz photo stimulation and a focused condition using 20 Hz photo stimulation, measuring the brain's EEG signal before and during the brain photo stimulation. Afterwards, the measured EEG signals were processed to obtain the frequency spectrum of before and during photo stimulation, which were compared to conclude if photo biomodulation interferes with the measurement of EEG signals and if there is an effect on brain function through the spectrum of EEG signals. Photo biomodulation was considered not to have interfered with EEG measurement, and a significant effect of photo biomodulation on the frequency spectrum of the EEG signal was observed in one subje

EMG KONTROLA ROBOTSKE RUKE

U ovom radu istražujemo nastanak EMG signala u tijelu čovjeka te osnovne mehanizme iza njegovog stvaranja, te definiramo moguće načine akvizicije EMG signala iz mišića, nadalje opisujemo karakteristike EMG signala. Prikazujemo već ostvarene sustave za upravljanje robotskom rukom pomoću EMG signala te prikazujemo njihove mogućnosti za upravljanje jednim takvim sustavom, deklariramo ih s obzirom na koliko mišića snimaju EMG signal i s obzirom na način obrade toga signala. Nakon toga predlažemo idejno rješenje jednog EMG sustava za kontrolu robotskom rukom, te prolazimo kroz sastavne dijelove objašnjavajući princip rada svakog, prikazujemo utjecaj na signal i određujemo vrijednosti potrebnih komponenata. Pomoću tih saznanja određujemo završnu shemu pomoću koje dizajniramo i izrađujemo tiskanu pločicu na koju onda postavljamo komponente, te prikazujemo način spajanja na EMG pločice na mikrokontroler.This paper researches the generation of EMG signals in the human body and the basic mechanisms behind its creation, defining the possible ways of acquisition of EMG signals from muscles and further describing the characteristics of the EMG signal. We present already realized control systems for a robotic arm using EMG signals and show their way of controlling a robotic arm, we declare them with a regard to how many muscles do we record the EMG signal from and with respect to the method of processing that signal. After that, we propose a conceptual design of a system for EMG control of a robotic arm, and go through the parts of the system explaining the principle of operation of each, show the influence of the signal and determine the value of the necessary components. We use these insights determine the final schematic with help of which we design and build a printed circuit board and we populate it with components, and then we show how to connect the microcontroller to the EMG board

Realization of device for IR head stimulation

U ovom radu opisan proces apsorpcije valnih duljina svijetlosti u fotoakceptorima na kojemu se temelji fotobiomodulacija, nabrojane su primjene fotobiomodulacije u medicini općenito, te su objašnjeni načini, istraživanja i moguće primjene fotobiomodulacije mozga. Nadalje, prikazan je komercijalan uređaj za fotobiomodulaciju mozga, te su objašnjeni pojedini parametri koji su krucijalni pri izvođenju pravilnog tretmana fotobiomodulacije. Nakon toga je napravljen dizajn kod kojega su proračunate i odabrane vrijednosti potrebnih elemenata, te je realiziran sklop za generiranje pravokutnog valnog oblika radnog ciklusa od 50% s mogućim odabirom između tri frekvencije modulacije napona i struje napajanja blisko infracrvenih svijetlećih dioda. Realizirani su LED klasteri spajanjem svijetlećih dioda u seriju radi smanjivanja gubitaka i uklanjanja potrebe za prilagodbu napona napajanja, koji su onda spojeni paralelno. Svi su moduli montirani na kacigu „Ultracortex IV“ kao nosivu strukturu, klasteri su pozicionirani na potrebna mjesta iznad željenih dijelova mozga koji se žele stimulirati, a napajanje je realizirano prijenosnim USB napajanjem radi jednostavnosti i lakšeg korištenja. Potom su izvedena mjerenja na dvije osobe pri dva različita stanja mozga, opušteno stanje pri kojem se koristila foto stimulacija od 10 Hz i koncentrirano stanje pri kojem se koristila foto stimulacija od 20 Hz, pri čemu se je mjerio EEG signal mozga prije i tijekom foto stimulacije mozga. Nakon toga su izmjereni EEG signali obrađeni na način da se dobije spektri frekvencija prije i tijekom foto stimulacije čijom usporedbom se došlo do zaključka ukoliko fotobiomodulacija radi smetnje mjerenju EEG signala te ukoliko postoji utjecaj na rad mozga odnosno na spektar EEG signala. Pri čemu se smatra da fotobiomodulacija nije radila smetnje na EEG te je kod jednog ispitanika zapažena značajan utjecaj fotobiomodulacije na spektar EEG signala.This paper describes the process of absorption of wavelengths of light in photo acceptors, on which photo biomodulation is based, lists the applications of photo biomodulation in medicine in general, and explains the methods, studies and possible applications of brain photo biomodulation. Furthermore, a commercial device for brain photo biomodulation is shown, and some parameters that are crucial in performing the proper photo biomodulation treatment are explained. After that, a circuit was designed and the values of the required elements were calculated and selected, circuit for generating a rectangular duty cycle waveform of 50% was realized, with a possible choice between three frequencies of modulating the supply voltage and current for the near-infrared LED-s. LED clusters were implemented by connecting LED-s in series to reduce losses and eliminate the need to adjust the supply voltage, which were then connected in parallel. All modules were mounted on the "Ultracortex IV" helmet as a load-bearing structure, the clusters are positioned in the necessary places above the desired parts of the brain to be stimulated, and the power is provided by using portable USB power because of its simplicity and ease of use. Measurements were made on two persons and were performed with two different brain states, a relaxed condition using 10 Hz photo stimulation and a focused condition using 20 Hz photo stimulation, measuring the brain's EEG signal before and during the brain photo stimulation. Afterwards, the measured EEG signals were processed to obtain the frequency spectrum of before and during photo stimulation, which were compared to conclude if photo biomodulation interferes with the measurement of EEG signals and if there is an effect on brain function through the spectrum of EEG signals. Photo biomodulation was considered not to have interfered with EEG measurement, and a significant effect of photo biomodulation on the frequency spectrum of the EEG signal was observed in one subje

Realization of device for IR head stimulation

U ovom radu opisan proces apsorpcije valnih duljina svijetlosti u fotoakceptorima na kojemu se temelji fotobiomodulacija, nabrojane su primjene fotobiomodulacije u medicini općenito, te su objašnjeni načini, istraživanja i moguće primjene fotobiomodulacije mozga. Nadalje, prikazan je komercijalan uređaj za fotobiomodulaciju mozga, te su objašnjeni pojedini parametri koji su krucijalni pri izvođenju pravilnog tretmana fotobiomodulacije. Nakon toga je napravljen dizajn kod kojega su proračunate i odabrane vrijednosti potrebnih elemenata, te je realiziran sklop za generiranje pravokutnog valnog oblika radnog ciklusa od 50% s mogućim odabirom između tri frekvencije modulacije napona i struje napajanja blisko infracrvenih svijetlećih dioda. Realizirani su LED klasteri spajanjem svijetlećih dioda u seriju radi smanjivanja gubitaka i uklanjanja potrebe za prilagodbu napona napajanja, koji su onda spojeni paralelno. Svi su moduli montirani na kacigu „Ultracortex IV“ kao nosivu strukturu, klasteri su pozicionirani na potrebna mjesta iznad željenih dijelova mozga koji se žele stimulirati, a napajanje je realizirano prijenosnim USB napajanjem radi jednostavnosti i lakšeg korištenja. Potom su izvedena mjerenja na dvije osobe pri dva različita stanja mozga, opušteno stanje pri kojem se koristila foto stimulacija od 10 Hz i koncentrirano stanje pri kojem se koristila foto stimulacija od 20 Hz, pri čemu se je mjerio EEG signal mozga prije i tijekom foto stimulacije mozga. Nakon toga su izmjereni EEG signali obrađeni na način da se dobije spektri frekvencija prije i tijekom foto stimulacije čijom usporedbom se došlo do zaključka ukoliko fotobiomodulacija radi smetnje mjerenju EEG signala te ukoliko postoji utjecaj na rad mozga odnosno na spektar EEG signala. Pri čemu se smatra da fotobiomodulacija nije radila smetnje na EEG te je kod jednog ispitanika zapažena značajan utjecaj fotobiomodulacije na spektar EEG signala.This paper describes the process of absorption of wavelengths of light in photo acceptors, on which photo biomodulation is based, lists the applications of photo biomodulation in medicine in general, and explains the methods, studies and possible applications of brain photo biomodulation. Furthermore, a commercial device for brain photo biomodulation is shown, and some parameters that are crucial in performing the proper photo biomodulation treatment are explained. After that, a circuit was designed and the values of the required elements were calculated and selected, circuit for generating a rectangular duty cycle waveform of 50% was realized, with a possible choice between three frequencies of modulating the supply voltage and current for the near-infrared LED-s. LED clusters were implemented by connecting LED-s in series to reduce losses and eliminate the need to adjust the supply voltage, which were then connected in parallel. All modules were mounted on the "Ultracortex IV" helmet as a load-bearing structure, the clusters are positioned in the necessary places above the desired parts of the brain to be stimulated, and the power is provided by using portable USB power because of its simplicity and ease of use. Measurements were made on two persons and were performed with two different brain states, a relaxed condition using 10 Hz photo stimulation and a focused condition using 20 Hz photo stimulation, measuring the brain's EEG signal before and during the brain photo stimulation. Afterwards, the measured EEG signals were processed to obtain the frequency spectrum of before and during photo stimulation, which were compared to conclude if photo biomodulation interferes with the measurement of EEG signals and if there is an effect on brain function through the spectrum of EEG signals. Photo biomodulation was considered not to have interfered with EEG measurement, and a significant effect of photo biomodulation on the frequency spectrum of the EEG signal was observed in one subje

Entropy-Based Concentration and Instantaneous Frequency of TFDs from Cohen’s, Affine, and Reassigned Classes

This paper explores three groups of time–frequency distributions: the Cohen’s, affine, and reassigned classes of time–frequency representations (TFRs). This study provides detailed insight into the theory behind the selected TFRs belonging to these classes. Extensive numerical simulations were performed with examples that illustrate the behavior of the analyzed TFR classes in the joint time–frequency domain. The methods were applied both on synthetic and real-life non-stationary signals. The obtained results were assessed with respect to time–frequency concentration (measured by the Rényi entropy), instantaneous frequency (IF) estimation accuracy, cross-term presence in the TFRs, and the computational cost of the TFRs. This study gives valuable insight into the advantages and limitations of the analyzed TFRs and assists in selecting the proper distribution when analyzing given non-stationary signals in the time–frequency domain