David Atienza Alonso

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

With ever-increasing power densities, Dynamic Thermal Management (DTM) techniques have become mainstream in today’s systems. An important component of such techniques is the thermal trigger. It has been shown that predictive thermal triggers can outperform ...

Wearable devices are an unobtrusive, cost-effective means of continuous ambulatory monitoring of chronic cardiovascular diseases. However, on these resource-constrained systems, electrocardiogram (ECG) processing algorithms must consume minimal power and m ...

This paper focuses on a review of state-of-the-art memory designs and new design methods for near-threshold computing (NTC). In particular, it presents new ways to design reliable low-voltage NTC memories cost-effectively by reusing available cell librarie ...

Among all cardiovascular diseases, congestive heart failure (CHF) has a very high rate of hospitalization and mortality. In order to prevent hospitalization, there is a strong need to identify patients at risk of a CHF event by estimating a set of relevant ...

This work is devoted to the evaluation of multilead digital wavelet transform (DWT)-based electrocardiogram (ECG) wave delineation algorithms, which were optimized and ported to a commercial wearable sensor platform. More specifically, we investigate the u ...

The design of low-power wearables for the biomedical domain has received a lot of attention in recent decades, as technological advances in chip manufacturing have allowed real-time monitoring of patients using low-complexity ML within the mW range. Despit ...

In this work, we present eXtendible Heterogeneous Energy-Efficient Platform (X-HEEP), a configurable and extendible single-core RISC-V-based ultra-low-power microcontroller. X-HEEP can be used standalone as a low-cost microcontroller, or it can be integrat ...

Chip designers place on-chip sensors to measure local temperatures, thus preventing thermal runaway situations in multicore processing architectures. However, thermal characterization is directly dependent on the number of placed sensors, which should be m ...

Technology scaling has offered advantages to embedded systems, such as increased performance, more available memory and reduced energy consumption. However, scaling also brings a number of problems like reliability degradation mechanisms. The intensive act ...

The increasing popularity of multi-core System-on-Chip platforms introduces new challenges, both in terms of hardware platforms and design methodologies. Dynamic reconfiguration can be exploited to increase the flexibility of the system and to implement mu ...

A method for remotely controlling an operated unmanned object, comprises defining of a set of control movements of an operator; selecting of minimal necessary signals to reliably acquire the operator's control movements; defining of a mapping of the contro ...

While Resistive Random Access Memories (RRAM) are perceived nowadays as a promising solution for the future of computing, these technologies suffer from intrinsic variability regarding programming voltage, switching speed and achieved resistance values. Wr ...

Compressed sensing (CS) is a universal technique for the compression of sparse signals. CS has been widely used in sensing platforms where portable, autonomous devices have to operate for long periods of time with limited energy resources. Therefore, an ul ...

State-of-the-art devices in the consumer electronics market are relying more and more on Multi-Processor Systems-On-Chip (MPSoCs) as an efficient solution to meet their multiple design constrains, such as low cost, low power consumption, high performance a ...

Detection and classification of human emotions from multiple bio-signals has a wide variety of applications. Though electronic devices are available in the market today that acquire multiple body signals, the classification of human emotions in real-time, ...

The photoplethysmographic (PPG) signal is an unobtrusive blood pulsewave measure that has recently gained popularity in the context of the Internet of Things. Even though it is commonly used for heart rate detection, it has been lately employed on multimod ...

Area and power constrained edge devices are increasingly utilized to perform compute intensive workloads, necessitating increasingly area and power efficient accelerators. In this context, in-SRAM computing performs hundreds of parallel operations on spati ...

A method for classification of ECG beats into normal and different categories of abnormal beats. The method comprises the following steps, performed on a computing platform: a. performing a training phase comprising taking as an input one or more ECG beats ...

Method for automatic online delineation of an electrocardiogram (ECG) bio signal, said method comprising the detection of said bio signal through several leads followed by the combination of those multiple acquisitions into a single root-mean-squared (RMS) ...

David Atienza Alonso

Chattez avec Graph Search

Run-Time Adaptable On-Chip Predictive Thermal Triggers

REWARD: Design, Optimization, and Evaluation of a Real-Time Relative-Energy Wearable R-Peak Detection Algorithm *

Resolving the Memory Bottleneck for Single Supply Near-Threshold Computing

Touch-Based System for Beat-to-Beat Impedance Cardiogram Acquisition and Hemodynamic Parameters Estimation

Development and Evaluation of Multi-Lead Wavelet-Based ECG Delineation Algorithms for Embedded Wireless Sensor Nodes

BiomedBench: A benchmark suite of TinyML biomedical applications for low-power wearables

X-HEEP: An Open-Source, Configurable and Extendible RISC-V Microcontroller

EigenMaps: Algorithms for Optimal Thermal Maps Extraction and Sensor Placement on Multicore Processors

Improving Reliability of Embedded Systems through Dynamic Memory Manager Optimization using Grammatical Evolution

Run-Time Mapping for Dynamically-Added Applications in Reconfigurable Embedded Systems

Teleoperation with a wearable sensor system

Write Termination circuits for RRAM : A Holistic Approach From Technology to Application Considerations

TamaRISC-CS: An Ultra-Low-Power Application-Specific Processor for Compressed Sensing

TheSPoT: Thermal Stress-Aware Power and Temperature Management for Multiprocessor Systems-on-Chip

Emulation-based transient thermal modeling of 2D/3D systems-on-chip with active cooling

Energy-Aware Embedded Classifier Design for Real-Time Emotion Analysis

SPARE: A Spectral Peak Recovery Algorithm for PPG Signals Pulsewave Reconstruction in Multimodal Wearable Devices

Blade: An in-Cache Computing Architecture for Edge Devices

Method for detecting abnormalities in an electrocardiogram

Automatic online delineation of a multi-lead electrocardiogram bio signal