
Mahya SafaviUniversity of California, Irvine | UCI · Department of Electrical Engineering and Computer Science
Mahya Safavi
Doctor of Philosophy
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13
Publications
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Introduction
Mahya Safavi currently works at the Department of Electrical Engineering and Computer Science, University of California, Irvine. Mahya does research in Electrical Engineering.
Publications
Publications (13)
The purpose of this study is to analyse the ictal variations in peripheral blood flow using photoplethysmogram (PPG) and single lead Electrocardiogram (ECG) signals. 11 subjects with 56 partial seizures were recorded with the PPG sensor worn on their left ankles. 6 different features from PPG pulse morphology related to hemodynamics were derived. T...
Objectives: This study examines human Photoplethysmogram (PPG) along with Electrocardiogram (ECG) signals to study cardiac autonomic imbalance in epileptic seizures. The significance and the prevalence of changes in PPG morphological parameters have been investigated to find common patterns among subjects. Alterations in cardiovascular parameters m...
This paper describes EcoMicro, a miniature, self-powered, wireless inertial-sensing node in the volume of 8 x 13 x 9.5 mm3, including energy storage and solar cells. It is smaller than existing systems with similar functionality while retaining rich functionality and efficiency. It is capable of measuring motion using a inertial measurement unit (I...
Objective:
Real-time implementation of EEG source localization can be employed in a broad area of applications such as clinical diagnosis of neurologic diseases and brain-computer interface. However, a power-efficient, low-complexity, and real-time implementation of EEG source localization is still challenging due to extensive iterations in the so...
This paper describes a wearable wireless mouse-cursor controller that optically tracks the degree of tilt of the user's head to move the mouse relative distances and therefore the degrees of tilt. The raw data can be processed locally on the wearable device before tirelessly transmitting the mouse-movement reports over Bluetooth Low Energy (BLE) pr...
Two techniques are proposed to alleviate the computational burden of MUltiple SIgnal Classification (MUSIC) algorithm applied to Electroencephalogram (EEG) source localization. A significant reduction was achieved by parsing the cortex surface into smaller regions and nominating only a few regions for the exhaustive search inherent in the MUSIC alg...
The feasibility of using infrared (IR) spectroscopy of the neck muscles in controlling a cursor in a 2-dimensional screen was assessed. The proposed technique utilizes two IR photoplethysmography sensors (λ = 940nm) to monitor the morphological changes of the Scalene and Sternocleidomastoid muscles. Since the reflection of the light has valuable in...
Two techniques are proposed to alleviate the computational burden of MUltiple SIgnal Classification (MUSIC) algorithm applied to Electroencephalogram (EEG) source localization. A significant reduction was achieved by parsing the cortex surface into smaller regions and nominating only a few regions for the exhaustive search inherent in the MUSIC alg...
A novel approach for decoding the finger flexion and extension from the human electrocorticogram is proposed. First, for different finger movements, we use projected MUltiple SIgnal Classification (projected MUSIC) as a source localization technique to estimate the active areas in the primary motor cortex. Next, in order to distinguish between the...
In this paper, a novel multiple antenna, high-resolution eigenvalue-based spectrum sensing algorithm based on the FFT of the received signal is introduced. The proposed platform overcomes the SNR wall problem in the conventional energy detection (ED) algorithm, enabling the detection of the weak signals at −10 dB SNR. Moreover, the utilization of F...
Signal to Noise and Distortion Ratio (SNDR) is widely chosen for dynamic characterization of ADC. For pipelined ADC in which the inner circuits' errors accumulate at the output, analysis of the origins of SNDR and its characterization can be very hard. However, due to a relationship between maximum INL of ADC and the distortion in its output codes,...
An Eigenvalue-based detection (EBD) scheme, is proposed as an efficient method to overcome the noise uncertainty and the SNR wall problem in conventional energy detection (ED) schemes. Despite remarkable efforts made to analyze the EBD performance, a VLSI implementation is missing in literature. In this paper, a new FFT-based EBD algorithm is intro...