Direct Memory Access-Based Data Storage for Long-Term Acquisition Using Wearables in an Energy-Efficient Manner

Cosmin C Dobrescu; Iván González; David Carneros-Prado; Jesús Fontecha; Christopher Nugent

doi:10.3390/s24154982

Direct Memory Access-Based Data Storage for Long-Term Acquisition Using Wearables in an Energy-Efficient Manner

Cosmin C Dobrescu
, Iván González
, David Carneros-Prado
, Jesús Fontecha
, Christopher Nugent

Castilla La Mancha University

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

73 Downloads (Pure)

Abstract

This study introduces a lightweight storage system for wearable devices, aiming to optimize energy efficiency in long-term and continuous monitoring applications. Utilizing Direct Memory Access and the Serial Peripheral Interface protocol, the system ensures efficient data transfer, significantly reduces energy consumption, and enhances the device autonomy. Data organization into Time Block Data (TBD) units, rather than files, significantly diminishes control overhead, facilitating the streamlined management of periodic data recordings in wearable devices. A comparative analysis revealed marked improvements in energy efficiency and write speed over existing file systems, validating the proposed system as an effective solution for boosting wearable device performance in health monitoring and various long-term data acquisition scenarios.

Original language	English
Article number	4982
Pages (from-to)	1-18
Number of pages	18
Journal	Sensors
Volume	24
Issue number	15
Early online date	1 Aug 2024
DOIs	https://doi.org/10.3390/s24154982
Publication status	Published online - 1 Aug 2024

Bibliographical note

Publisher Copyright:
© 2024 by the authors.

Data Availability Statement

The measurements of electrical consumption, which were collected and analyzed for this study, will be available at https://zenodo.org/doi/10.5281/zenodo.13143215 (accessed on 29 July 2024).

Funding

This research was funded by two projects: Grant PDC2022-133457-I00 (sSITH: Self-recharging Sensorized Insoles for Continuous Long-Term Human Gait Monitoring), funded by MCIN/AEI and supported by funds from the European Union’s NextGeneration EU/PRTR. The project ran from 1 December 2022 to 30 November 2024. Grant PID2022-142388OA-I00 (“Just move!”: Early detection of MCI through human-movement analysis in everyday life JUST-MOVE), funded by MCIN/AEI/10.13039/501100011033 and by “European Union NextGenerationEU/PRTR”. The project ran from 1 September 2023 to 31 August 2026. In addition, thank you for the funding for the research stay call in Universities and Research centres abroad for full-time teaching staff (2023). BDNS (Identifier): 660787. [2022/10970] by the “Plan Propio de Investigación” of the University of Castilla-La Mancha.

Funders	Funder number
Universidad de Castilla-La Mancha
660787, MCIN/AEI/10.13039/501100011033, 2022/10970
PID2022-142388OA-I00

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

long-term monitoring
Continuous Monitoring
Wearable Devices
Dma Controller
Embedded Storage Management
Ultra-low Power Data Storage
continuous monitoring
wearable devices
ultra-low power data storage
DMA controller
embedded storage management

Access to Document

10.3390/s24154982

sensors-24-04982Final published version, 1.02 MBLicence: CC BY

Cite this

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abstract = "This study introduces a lightweight storage system for wearable devices, aiming to optimize energy efficiency in long-term and continuous monitoring applications. Utilizing Direct Memory Access and the Serial Peripheral Interface protocol, the system ensures efficient data transfer, significantly reduces energy consumption, and enhances the device autonomy. Data organization into Time Block Data (TBD) units, rather than files, significantly diminishes control overhead, facilitating the streamlined management of periodic data recordings in wearable devices. A comparative analysis revealed marked improvements in energy efficiency and write speed over existing file systems, validating the proposed system as an effective solution for boosting wearable device performance in health monitoring and various long-term data acquisition scenarios.",

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AU - Nugent, Christopher

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Direct Memory Access-Based Data Storage for Long-Term Acquisition Using Wearables in an Energy-Efficient Manner

Abstract

Bibliographical note

Data Availability Statement

Funding

UN SDGs

Keywords

Access to Document

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Cite this