Papers

@article{rodriguez_wearable_2021,

title = {Wearable Postural Control System for Low Back Pain Therapy},

author = {Alvaro Rodriguez and Juan R. Rabuñal-Dopico and Alejandro Pazos and Antonio Rodríguez Sotillo and Norberto Ezquerra},

url = {https://ieeexplore.ieee.org/document/9351989},

doi = {10.1109/TIM.2021.3057935},

issn = {1557-9662},

year  = {2021},

date = {2021-01-01},

urldate = {2026-08-07},

journal = {IEEE Transactions on Instrumentation and Measurement},

volume = {70},

pages = {1–10},

abstract = {Treatment of low back pain usually includes exercise, analgesics, prostheses, and, in severe cases, surgery. Early treatments based on postural control are essential to prevent low back pain and mitigate permanent damage. We present a wearable device, with an estimated cost below U.S. $100, which uses inertial units with triaxial accelerometers, gyroscopes, and magnetometers to measure the orientation of three sections of the spine. The device integrates the absolute and relative orientation from the sensors to estimate the posture of the back in real-time and uses a fuzzy system to control a vibration unit that indicates the user when to correct the posture of the back. We validated the device in controlled conditions, obtaining an rms deviation ≤1.24° and conducted a preliminary clinical pilot study with patients afflicted by lumbar hyperlordosis or lumbar hypolordosis. We observed an improved postural control and a reduction of low back pain in all cases. These results show a promising potential of the device to reduce pain, improve postural therapies, and raise postural awareness in patients affected with low back pain.},

keywords = {Accelerometers, Back, Back orientation, fuzzy system, Gyroscopes, inertial measurement unit (IMU), low back pain, Medical treatment, Monitoring, Pain, posture therapy, Spine},

pubstate = {published},

tppubtype = {article}

}

@article{Alvarellos2020,

title = {Developing a secure low-cost radon monitoring system},

author = {Alberto Alvarellos-González and Marcos Gestal and Julián Dorado and Juan R. Rabuñal-Dopico},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078903262&doi=10.3390%2fs20030752&partnerID=40&md5=37a4e893986d8e10605c71bd81697d44},

doi = {10.3390/s20030752},

issn = {14248220},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

journal = {Sensors (Switzerland)},

volume = {20},

number = {3},

publisher = {MDPI AG},

abstract = {Radon gas has been declared a human carcinogen by the United States Environmental Protection Agency (USEPA) and the International Agency for Research on Cancer (IARC). Several studies carried out in Spain highlighted the high radon concentrations in several regions, with Galicia (northwestern Spain) being one of the regions with the highest radon concentrations. The objective of this work was to create a safe and low-cost radon monitoring and alert system, based on open source technologies. To achieve this objective, the system uses devices, a collection of sensors with a processing unit and a communication module, and a backend, responsible for managing all the information, predicting radon levels and issuing alerts using open source technologies. Security is one of the largest challenges for the internet of things, and it is utterly important in the current scenario, given that high radon concentrations pose a health risk. For this reason, this work focuses on securing the entire end-to-end communication path to avoid data forging. The results of this work indicate that the development of a low-cost, yet secured, radon monitoring system is feasible, allowing one to create a network of sensors that can help mitigate the health hazards that high radon concentrations pose. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.},

note = {cited By 17},

keywords = {Air Pollution, Alert systems; End-to-End communication; International agency for research on cancers; IoT security; Open sources; Open-source technology; Radon monitoring; United states environmental protection agencies, Costs; Environmental Protection Agency; Health hazards; Health risks; International cooperation; Internet of things; Open systems; Radon; Risk perception, environmental exposure; environmental monitoring; human; indoor air pollution; isolation and purification; prevention and control; risk factor; Spain; United States, Indoor; Environmental Exposure; Environmental Monitoring; Humans; Radon; Risk Factors; Spain; United States, Monitoring, radon},

pubstate = {published},

tppubtype = {article}

}

@article{cillero_castro_uav_2020,

title = {An UAV and Satellite Multispectral Data Approach to Monitor Water Quality in Small Reservoirs},

author = {Carmen Cillero-Castro and Jose Antonio Domínguez-Gómez and Jordi Delgado-Martín and Boris Alejandro Hinojo-Sánchez and José Luis Cereijo-Arango and Federico Andrés Cheda Tuya and Ramon Díaz-Varela},

url = {https://www.mdpi.com/2072-4292/12/9/1514},

doi = {10.3390/rs12091514},

issn = {2072-4292},

year  = {2020},

date = {2020-01-01},

urldate = {2026-08-06},

journal = {Remote Sensing},

volume = {12},

number = {9},

pages = {1514},

publisher = {Multidisciplinary Digital Publishing Institute},

abstract = {A multi-sensor and multi-scale monitoring tool for the spatially explicit and periodic monitoring of eutrophication in a small drinking water reservoir is presented. The tool was built with freely available satellite and in situ data combined with Unmanned Aerial Vehicle (UAV)-based technology. The goal is to evaluate the performance of a multi-platform approach for the trophic state monitoring with images obtained with MultiSpectral Sensors on board satellites Sentinel 2 (S2A and S2B), Landsat 8 (L8) and UAV. We assessed the performance of three different sensors (MultiSpectral Instrument (MSI), Operational Land Imager (OLI) and Rededge Micasense) for retrieving the pigment chlorophyll-a (chl-a), as a quantitative descriptor of phytoplankton biomass and trophic level. The study was conducted in a waterbody affected by cyanobacterial blooms, one of the most important eutrophication-derived risks for human health. Different empirical models and band indices were evaluated. Spectral band combinations using red and near-infrared (NIR) bands were the most suitable for retrieving chl-a concentration (especially 2 band algorithm (2BDA), the Surface Algal Bloom Index (SABI) and 3 band algorithm (3BDA)) even though blue and green bands were useful to classify UAV images into two chl-a ranges. The results show a moderately good agreement among the three sensors at different spatial resolutions (10 m., 30 m. and 8 cm.), indicating a high potential for the development of a multi-platform and multi-sensor approach for the eutrophication monitoring of small reservoirs.},

keywords = {eutrophication, Monitoring, multispectral imagery, satellite, UAV, Water quality},

pubstate = {published},

tppubtype = {article}

}