David Atienza Alonso

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It is widely recognized today that there is an alarming rise of lifestyle-induced chronic diseases (e.g., type II diabetes) in our society. Therefore, a strong need exists for cost-effective and non-invasive devices that can measure blood pressure (BP) to ...

Objective To develop and validate a wrist‐worn accelerometer‐based, deep‐learning tunable algorithm for the automated detection of generalized or bilateral convulsive seizures (CSs) to be integrated with off‐the‐shelf smartwatches. Methods We conducted a ...

Recent advances in process technology augment the systems-on-chip (SoCs) functionality per unit area with the substantial decrease of device features. However, features abatement triggers new reliability issues such as the single-event multi-bit upset (SMU ...

Current systems-on-chip (SoC) execute applications that demand extensive parallel processing. Networks-on-chip (NoC) provide a structured way of realizing interconnections on silicon, and obviate the limitations of bus-based solutions. NoC can have regular ...

In this paper we investigate the impact of potential hardware misbehavior induced by reliability issues and scaled voltages in wireless body sensor network (WBSN) nodes. Our study reveals the inherent resilience of popular algorithms in cardiac monitoring ...

In the Internet-of-Things (IoT) era, there is an increasing trend to enable intelligent behavior in edge computing sensors. Thus, a new generation of smart wearable devices for health monitoring is being developed, able to perform complex Digital Signal Pr ...

Smart edge sensors for bio-signal monitoring must support complex signal processing routines within an extremely small energy envelope. Coarse-Grained Reconfigurable Arrays (CGRAs) are good candidates for tackling these conflicting objectives because, than ...

Wireless body sensor networks (WBSN) hold the promise to be a key enabling information and communications technology for next-generation patient-centric tele-cardiology or mobile cardiology solutions. Through enabling continuous remote cardiac monitoring, ...

Three-dimensional (3D) circuits reduce communication delay in multicore SoCs, and enable efficient integration of cores, memories, sensors, and RF devices. However, vertical integration of layers exacerbates the reliability and thermal problems, and coolin ...

In the last years, remote health monitoring is becoming an essential branch of health care with the rapid development of wearable sensors technology. To meet the demand of new more complex applications and ensuring adequate battery lifetime, wearable senso ...

The rapid development of wearable biomedical systems now enables real-time monitoring of electroencephalography (EEG) signals. Acquisition of these signals relies on electrodes. These systems must meet the design challenge of selecting an optimal set of el ...

The equivalent English title: "Design of Custom Networks-on-Chip with Physical Layout Information" Abstract translated into English: Due to the growing demand of communication between processors and memory devices in Systems-on-Chip (SoCs), recently the ne ...

With the surge in complexity of edge workloads, it appeared in the scientific community that such workloads cannot be anymore overflown to the cloud due to the huge edge device to server communication energy cost and the high energy consumption induced in ...

Wearable IoT devices and novel continuous monitoring algorithms are essential components of the healthcare transition from reactive interventions focused on symptom treatment to more proactive prevention, from one-size-fits-all to personalized medicine, an ...

As processor performance advances, increasing power densities and complex thermal behaviors threaten both energy efficiency and system reliability. This survey covers more than two decades of research on power and thermal modeling and management in modern ...

Aging effects in digital circuits change the switching characteristics of their transistors, resulting in timing violations that can lead to functional errors at the system level. In particular, BTI is a degradation effect that changes the threshold voltag ...

Powder bed fusion with laser beam (PBF-LB) is a promising additive manufacturing technique that enables the production of complex geometries with fine resolution and material efficiency, offering significant design freedom and material versatility. However ...

Low-power wearable technologies offer a promising solution to pervasive epilepsy monitoring by removing the constraints concerning time and location, on one hand, and fulfilling long-term tracking, on the other hand. In the case of epileptic seizures, as t ...

The long-standing analog-to-digital conversion paradigm based on Shannon/Nyquist sampling has been challenged lately, mostly in situations such as radar and communication signal processing where signal bandwidth is so large that sampling architectures cons ...

David Atienza Alonso

Chattez avec Graph Search

Estimation of Blood Pressure and Pulse Transit Time Using Your Smartphone

Deep learning–based detection of generalized convulsive seizures using a wrist‐worn accelerometer

A Hybrid HW-SW Approach for Intermittent Error Mitigation in Streaming-Based Embedded Systems

A Complete Network-On-Chip Emulation Framework

Design of Energy Efficient and Dependable Health Monitoring Systems under Unreliable Nanometer Technologies

Heterogeneous and Inexact: Maximizing Power Efficiency of Edge Computing Sensors for Health Monitoring Applications

i-DPs CGRA: An Interleaved-Datapaths Reconfigurable Accelerator for Embedded Bio-signal Processing

ReLearn: A Robust Machine Learning Framework in Presence of Missing Data for Multimodal Stress Detection from Physiological Signals

Compressed Sensing for Real-Time Energy-Efficient ECG Compression on Wireless Body Sensor Nodes

Modeling and Dynamic Management of 3D Multicore Systems with Liquid Cooling

Modular Design and Optimization of Biomedical Applications for Ultra-Low Power Heterogeneous Platforms

FETCH: A Fast and Efficient Technique for Channel Selection in EEG Wearable Systems

Diseño de redes en chip de propósito específico con información de rutado físico

Functionality Enhanced Memories for Edge-AI Embedded Systems

ExG Signal Feature Selection Using Hyperdimensional Computing Encoding

A 20-Year Retrospective on Power and Thermal Modeling and Management

Analysis of Functional Errors Produced by Long-Term Workload-Dependent BTI Degradation in Ultra-Low Power Processors

Autonomous exploration of the PBF-LB parameter space: An uncertainty-driven algorithm for automated processing map generation

Self-Aware Anomaly-Detection for Epilepsy Monitoring on Low-Power Wearable Electrocardiographic Devices

Design and Exploration of Low-Power Analog to Information Conversion Based on Compressed Sensing