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Electrocardiogram (ECG), Electrodermal Activity (EDA), Electromyogram (EMG) and Impedance Cardiography (ICG) are among physiological signals widely used in various biomedical applications including health tracking, sleep quality assessment, early disease detection/diagnosis and human affective state recognition. This paper presents the development of a biosignal-specific processing and feature extraction...
Tripolar concentric ring electrode (TCRE) sensors have unique properties. These sensors have been used to acquire various bio-signals such as: electroencephalography (EEG), electrocardiography (ECG), and electromyography (EMG). Compared to conventional disc electrode signals TCRE EEG (tEEG) has four times better signal-to-noise ratio, eleven times better mutual information and spatial resolution....
One of the difficulties in implementing family medicine is the number of people per physician. This large number of enrollees makes preventive health services unavailable due to forcing physicians to do only outpatient services. In this study, it is aimed to realize the Family Physician Monitoring S ystem which will enable early intervention to the diseases that may occur by watching realtime medical...
With the advent of IoT and growing health awareness, the applications of wearable ECG & EMG sensors have grown manifold. These applications demand the sensors to be low-cost, low-power and highly portable. These requirements put several limitations on the wearable ECG & EMG sensors design and development. This paper presents a new ECG & EMG sensor which had power consumption less than...
The objective of this paper is to present a real time bio-telemetry system using LabVIEW, which acquires, analyzes and processes physiological parameters such as Electromyogram and Blood Pressure. This system enables continuous monitoring of a patient, which in turn helps the doctor to make a better diagnosis, thus ensuring mobility of both the patient and the doctor. In this proposed system we have...
Abnormality of the driver's Bio-physiological parameters has great impact on the driver's capability, and the ability to control a vehicle; which may cause severe car accidents. In this paper, a novel system was developed to monitor the driver's health status through a Wearable Bio-Sensors Bracelet that detects heath emergency threatening situations. The system collects live bio-signals data through...
Wearable devices for real-time ECG monitoring and analysis require an accurate but simple QRS detection algorithm which does not consume too much computational load. Dual-threshold QRS detection techniques are one of the promising solutions to overcome this problem. This study investigates the performance and robustness of a dual-threshold QRS detection method under different levels of noise and physical...
This paper presented a packet neural network identify and analysis elders fall situation in wearable device. The older human signal analysis have been a research topic health care fields that algorithms build in wearable device real time detect fall situation. The neural network used neurons weight to identify human fall situation, and we also utilize packet neurons methods to adjust weight that grouped...
In this study, Electrooculogram (EOG) based Human-Machine Interface (HMI) application is proposed for partial or completely paralyzed and physically limited people as Amyotrophic Lateral Sclerosis (ALS) patients. In the designed system, EOG signals consisted of vertical and horizontal eye movements are detected by using 6 Ag-AgCl electrodes which placed around the eye. Then, by applying amplifying...
Human visual system detects details in coloured images better. Sometimes interpretation of details in gray scale ultrasound images becomes harder. So in this work pseudocoloring of ultrasound images using empirical mode decomposition (EMD) is proposed. EMD doesn't use base function so it has more advantages than Fourier and wavelet transforms. The proposed method pseudocolored image by assigning two...
This paper deals with the development of unique human health monitoring system which can collect various health parameters from the patient and transmits the data over the internet for health monitoring system. This system works in two modes namely adult patient monitoring mode and child monitoring mode.
Nowadays, the majority of the monitoring devices used in clinical settings is limited to specific applications and powered by highly specialized microcontrollers and pre-programmed DSP systems. Moreover, these kind of devices are usually connected to a high capacity battery to operate in case of power blackout. Nevertheless, considering that all the measured bio-signals depends from an amperometric...
The recognition of human emotions using physiological signals such as Electrodermal Activity (EDA), Electrocardiogram (ECG) or Electromyography (EMG), has been extensively researched in the past attracting a lot of interest during the last few decades. Although showing a relatively satisfactory performance under lab conditions, Emotion Recognition (ER) systems using physiological signals are not widely...
Physical indicators are directly related with health and fitness of human body. By employing real-time e-health monitoring systems for acquiring, and analyzing bio-signals by measurements such as electrocardiogram (ECG) and electromyography (EMG), it is possible to extract information to achieve better health-care in terms of observation, diagnosis, and treatment. However, those systems are limited...
Emotions and affect are universal means of expressing the physiological state of an individual. Most of our daily interactions with other individuals involve emotions as an integral part. It has become highly prominent in technological research, as new technologies related to human-machine interaction or medical applications are developed. Detecting and analyzing emotions have become quite an important...
Biometric authentication technologies aim to increase the precision of security systems and have given proof of their effectiveness. Cognitive biometrics, in particular, has shown the potential of raising security levels, although lacking somewhat in terms of precision and adequate research. Therefore, this study analyses the viability of the usage of the Pointer Dynamics biometric technique as cognitive...
Our study aimed to determine hemispheric differences using Galvanic Skin Response (GSR) which is measure to emotional sweating with signal processing and feature extraction methods. Active sportsmans (n=17) and non-sportsmans (n=21) who are student at university have been used in this study. The average of ages is 20±0.4. We worked on GSR records which have been denoise with signal processing method...
The measurement of bio-signals is an important tool not only to assess the physical fitness, but also to prevent and/or to anticipate clinical episodes. In this paper a prototype to collect biosignals in water environments is described. This prototype collects three different signals such as accelerometry, electrocardiography, and electromyography, and was developed based on a modified off-the-shelf...
The automatic recognition of human emotions from physiological signals is of increasing interest in many applications. Images with high emotional content have been shown to alter signals such as the electrocardiogram (ECG) and the respiration among many other physiological recordings. However, recognizing emotions from multimedia stimuli, such as music video clips, which are growing in numbers in...
If an early predictor of motor functional outcome after stroke were available, stroke patients would receive more appropriate treatments for motor recovery. We performed a correlation analysis of the electroencephalography (EEG) signal patterns of nine subacute stroke patients (recorded 22.9 ± 7.1 days after onset) and their motor recovery rates (measured 100.2 ± 8.9 days after onset). The beta band...
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