Wyniki wyszukiwania - BazTech

Ograniczanie wyników

Powiadomienia systemowe

Sesja wygasła!
Sesja wygasła!
Sesja wygasła!

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: PPG

Sortuj według:

Ogranicz wyniki do:

Heart-rate Monitoring System Design and Analysis Using a Nios II Soft-core Processor

Lim C. K., Jambek A.B., Hashim U.

International Journal of Electronics and Telecommunications

2016

Vol. 62, No. 3

283--288

The heart rate of a person is able to tell whether they are healthy. A heart-rate monitoring device is able to measure or record the heart rate of a person in real time, whether it is an electrocardiogram (ECG) or a photoplethysmogram (PPG). In this work, a microprocessor system loaded with a heart-rate monitoring algorithm is implemented. The microprocessor system is the Nios II processor system, which interfaces with an analogue-to-digital converter (ADC) and a pulse sensor. A beat-finding algorithm is used in the microprocessor system for heart rate measurement. An experiment is carried out to analyse the functionality of the microprocessor system loaded with the algorithm. The results show that the detected heart rate is in the range of the average human being’s heart rate. The signal flow within the microprocessor system is observed and analysed using SignalTap II from Quartus’ software. Based on a power analysis report, the proposed microprocessor system has a total power dissipation of around 218.26 mW.

Detekcja błędów segmentacji sygnału fotopletyzmograficznego

Bołtrukiewicz M.

Pomiary Automatyka Kontrola

2014

R. 60, nr 8

541--543

Tematyka pracy związana jest z analizą zmienności rytmu serca, a dotyczy w szczególności detekcji błędów powstających podczas segmentacji procedury wyznaczającej zbiór okresów przebiegu. W artykule omówiono i zilustrowano podstawowe przyczyny błędów segmentacji. Zaproponowano dwa algorytmy detekcyjne wykorzystujące statystyczne przedziały tolerancji, które następnie przetestowano i oceniono przy użyciu posiadanego zbioru 5-minutowych przebiegów sygnału fotopletyzmograficznego.

The paper concerns the detection of segmentation errors in a photoplethysmographic signal (PPG). In the paper, the causes of segmentation errors are considered. The technical causes are presented in Figs. 1 and 2 while the biological causes are shown in Fig. 3. Two algorithms of detection of errors are proposed. Both algorithms use statistical tolerance ranges, which are described by Eq. 1. The principles of operation of these algorithms are given in Eqs. 2 and 3. In the study the efficiency of these algorithms was evaluated using the factor of errors defined by Eq. 4. For both algorithms the sensitivity (SE), specificity (SP) and positive prediction value (PPV) and negative prediction value (NPV) were calculated, too. In the experiments real photoplethysmographic signals were analyzed. Time duration of each signal was equal to 5 min. The coefficients of errors obtained for both algorithms are presented in Fig. 4. The comparison of the sensitivity and the positive prediction value is shown in Fig. 5. The causes of differences between the obtained values of the coefficients are considered. The possibility of improvement of SE and PPV is also analyzed.