0000000000173269
AUTHOR
Keisuke Nakamura
showing 7 related works from this author
Remote Photoplethysmography measurement using constrained ICA
2017
Remote Photoplethysmography (rPPG) is a technique that consists in estimating physiological parameters such as heart rate from live or recorded video sequences taken by conventional camera or even webcams. This technique is increasingly used in many application fields thanks to its simplicity and affordability. The basic idea is that the arterial blood flow shows regularity due to the heartbeat. This regularity is manifested by very small periodic variations in the color of the skin, which can be isolated and quantified by signal and image processing methods. In this context, Independent Component Analysis (ICA) is largely used to separate the signal due to arterial flow from signals from o…
Remote heart rate variability for emotional state monitoring
2018
International audience; Several researches have been conducted to recognize emotions using various modalities such as facial expressions , gestures, speech or physiological signals. Among all these modalities, physiological signals are especially interesting because they are mainly controlled by the autonomic nervous system. It has been shown for example that there is an undeniable relationship between emotional state and Heart Rate Variability (HRV). In this paper, we present a methodology to monitor emotional state from physiological signals acquired remotely. The method is based on a remote photoplethysmography (rPPG) algorithm that estimates remote Heart Rate Variability (rHRV) using a …
Parameter-free adaptive step-size multiobjective optimization applied to remote photoplethysmography
2018
International audience; In this work, we propose to reformulate the objective function of Independent Component Analysis (ICA) to make it a better posed problem in the context of Remote photoplethysmography (rPPG). In recent previous works, linear combination coefficients of RGB channels are estimated maximizing the non-Gaussianity of ICA output components. However, in the context of rPPG a priori knowledge of the pulse signal can be incorporated into the component extraction algorithm. To this end, the contrast function of regular ICA is extended with a measure of periodicity formulated using autocorrelation. This novel semi-blind source extraction method for measuring rPPG has the interes…
Comparison of region of interest segmentation methods for video-based heart rate measurements
2018
International audience; Conventional contact photoplethysmography (PPG) sensors are not suitable in situations of skin damage or when unconstrained movement is required. As a consequence, remote photoplethysmography (rPPG) has recently emerged because it provides remote physiological measurements without expensive hardware and improves comfort for long-term monitoring. RPPG estimation methods use the spatially averaged RGB values of pixels in a Region Of Interest (ROI) to generate a temporal RGB signal. The selection of ROI is a critical first step to obtain reliable pulse signals and must contain as many skin pixels as possible with a low percentage of non-skin pixels. In this paper, we ex…
Real-Time Temporal Superpixels for Unsupervised Remote Photoplethysmography
2018
International audience; Segmentation is a critical step for many computer vision applications. Among them, the remote photoplethys-mography technique is significantly impacted by the quality of region of interest segmentation. With the heart-rate estimation accuracy, the processing time is obviously a key issue for real-time monitoring. Recent face detection algorithms can perform real-time processing, however for unsupervised algorithms, i.e. without any subject detection based on supervised learning, existing methods are not able to achieve real-time on regular platform. In this paper, we propose a new method to perform real-time un-supervised remote photoplethysmograhy based on efficient…
An Embedded Solution for Multispectral Palmprint Recognition
2018
Palmprint based identification has attracted much attention in the past decades. In some real-life applications, portable personal authentication systems with high accuracy and speed efficiency are required. This paper presents an embedded palmprint recognition solution based on the multispectral image modality. We first develop an effective recognition algorithm by using partial least squares regression, then a FPGA prototype is implemented and optimized through high-level synthesis technique. The evaluation experiments demonstrate that the proposed system can achieve a higher recognition rate at a lower running cost comparing to the reference implementations.
Real-Time Temporal Superpixels for Unsupervised remote photopletysmography
2018
International audience