Miguel Damas

3.1k total citations · 1 hit paper
55 papers, 1.8k citations indexed

About

Miguel Damas is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering. According to data from OpenAlex, Miguel Damas has authored 55 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 16 papers in Computer Vision and Pattern Recognition and 14 papers in Electrical and Electronic Engineering. Recurrent topics in Miguel Damas's work include Context-Aware Activity Recognition Systems (15 papers), Non-Invasive Vital Sign Monitoring (9 papers) and Evolutionary Algorithms and Applications (8 papers). Miguel Damas is often cited by papers focused on Context-Aware Activity Recognition Systems (15 papers), Non-Invasive Vital Sign Monitoring (9 papers) and Evolutionary Algorithms and Applications (8 papers). Miguel Damas collaborates with scholars based in Spain, Colombia and United Kingdom. Miguel Damas's co-authors include H. Pomares, Oresti Baños, Ignacio Rojas, Juan Manuel Gálvez, Jesús González, Claudia Villalonga, Juan A. Holgado-Terriza, Julio Ortega, Rafael B. García and Sungyong Lee and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Expert Systems with Applications.

In The Last Decade

Miguel Damas

54 papers receiving 1.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Window Size Impact in Human Activity Recognition

2014 479 citations Oresti Baños, Juan Manuel Gálvez et al. Sensors profile →

Peers

Miguel Damas

CVPR

BE

AI

CNC

EEE

Oresti Baños Spain

Anthony Fleury France

Matjaž Gams Slovenia

Adil Khan Russia

Ahmad Lotfi United Kingdom

Paolo Napoletano Italy

Sakorn Mekruksavanich Thailand

Xiaohui Peng China

Anuchit Jitpattanakul Thailand

Mitja Luštrek Slovenia

Oresti Baños Spain

Miguel Damas

1.1k ×1.3

CVPR

626 ×1.2

BE

413 ×1.0

AI

408 ×1.3

CNC

287 ×1.1

EEE

Citations per year, relative to Miguel Damas Miguel Damas (= 1×) peers Oresti Baños

Countries citing papers authored by Miguel Damas

Since Specialization

Citations

This map shows the geographic impact of Miguel Damas's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Miguel Damas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Miguel Damas more than expected).

Fields of papers citing papers by Miguel Damas

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Miguel Damas. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Miguel Damas. The network helps show where Miguel Damas may publish in the future.

Co-authorship network of co-authors of Miguel Damas

This figure shows the co-authorship network connecting the top 25 collaborators of Miguel Damas. A scholar is included among the top collaborators of Miguel Damas based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Miguel Damas. Miguel Damas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Holgado-Terriza, Juan A., et al.. (2025). Forecasting Residential Energy Consumption with the Use of Long Short-Term Memory Recurrent Neural Networks. Energies. 18(5). 1247–1247. 4 indexed citations

2.

Damas, Miguel, et al.. (2023). A Deep Learning Model of Radio Wave Propagation for Precision Agriculture and Sensor System in Greenhouses. Agronomy. 13(1). 244–244. 11 indexed citations

3.

Holgado-Terriza, Juan A., et al.. (2023). Characterisation of Youth Entrepreneurship in Medellín-Colombia Using Machine Learning. Sustainability. 15(13). 10297–10297. 2 indexed citations

4.

Escobar, Juan José, Francisco Rodríguez, Beatriz Prieto, et al.. (2023). A distributed and energy-efficient KNN for EEG classification with dynamic money-saving policy in heterogeneous clusters. Computing. 105(11). 2487–2510. 5 indexed citations

5.

Postigo-Martín, Paula, Miguel Damas, H. Pomares, et al.. (2021). ATOPE+: An mHealth System to Support Personalized Therapeutic Exercise Interventions in Patients With Cancer. IEEE Access. 9. 16878–16898. 8 indexed citations

6.

Holgado-Terriza, Juan A., et al.. (2021). Radio Wave Attenuation Measurement System Based on RSSI for Precision Agriculture: Application to Tomato Greenhouses. Inventions. 6(4). 66–66. 10 indexed citations

7.

Damas, Miguel, et al.. (2021). 5G Mobile Phone Network Introduction in Colombia. Electronics. 10(8). 922–922. 10 indexed citations

8.

Damas, Miguel, et al.. (2020). Empirical Model of Radio Wave Propagation in the Presence of Vegetation inside Greenhouses Using Regularized Regressions. Sensors. 20(22). 6621–6621. 17 indexed citations

9.

Baños, Oresti, Miguel Damas, H. Pomares, et al.. (2020). CoVidAffect, real-time monitoring of mood variations following the COVID-19 outbreak in Spain. Scientific Data. 7(1). 365–365. 6 indexed citations

10.

Escobar, Juan José, Andrés Ortíz, Julio Ortega, et al.. (2020). Deep learning for EEG-based Motor Imagery classification: Accuracy-cost trade-off. PLoS ONE. 15(6). e0234178–e0234178. 45 indexed citations

11.

Damas, Miguel, et al.. (2019). Smartphone-Based Platform for Affect Monitoring through Flexibly Managed Experience Sampling Methods. Sensors. 19(15). 3430–3430. 10 indexed citations

12.

Damas, Miguel, et al.. (2019). Path Loss Determination Using Linear and Cubic Regression Inside a Classic Tomato Greenhouse. International Journal of Environmental Research and Public Health. 16(10). 1744–1744. 33 indexed citations

13.

Damas, Miguel, et al.. (2018). Intelligent Monitoring of Affective Factors Underlying Sport Performance by Means of Wearable and Mobile Technology. SHILAP Revista de lepidopterología. 1202–1202. 5 indexed citations

14.

Escobar, Juan José, Julio Ortega, A. F. Díaz, Jesús González, & Miguel Damas. (2018). Energy‐aware load balancing of parallel evolutionary algorithms with heavy fitness functions in heterogeneous CPU‐GPU architectures. Concurrency and Computation Practice and Experience. 31(6). 11 indexed citations

15.

Damas, Miguel, et al.. (2018). SPIRA: an automatic system to support lower limb injury assessment. Journal of Ambient Intelligence and Humanized Computing. 10(6). 2111–2123. 6 indexed citations

16.

Baños, Oresti, et al.. (2014). PhysioDroid: Combining Wearable Health Sensors and Mobile Devices for a Ubiquitous, Continuous, and Personal Monitoring. The Scientific World JOURNAL. 2014. 1–11. 63 indexed citations

17.

Baños, Oresti, Juan Manuel Gálvez, Miguel Damas, et al.. (2014). Evaluating the effects of signal segmentation on activity recognition.. 759–765. 7 indexed citations

18.

Baños, Oresti, et al.. (2013). PhysioDroid: an app for physiological data monitoring.. 297–304. 1 indexed citations

19.

Damas, Miguel, et al.. (2012). Ambient Assisted Living Devices Interoperability Based on OSGi and the X73 Standard. Telemedicine Journal and e-Health. 19(1). 54–60. 10 indexed citations

20.

Pomares, H., Ignacio Rojas, Jesús González, et al.. (2002). A two-stage approach to self-learning direct fuzzy controllers. International Journal of Approximate Reasoning. 29(3). 267–289. 19 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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