# Application of Machine Learning and Deep Learning Methods on ECG Sensor Data to Predict Stress Levels in Minimally Invasive Surgery

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/application-of-machine-learning-and-deep-learning-methods-on-ecg-sensor-data-to/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Daniel Caballero,Manuel J. Pérez-Salazar,Juan A. Sánchez‐Margallo,Ismael Diaz-Romero,Francisco M. Sánchez‐Margallo |
| Citations | 1 |
| DOI | 10.1007/978-3-032-10661-2_15 |
| Fields | Engineering,Medicine |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W7117968979 |
| Type | conference-paper |
| Year | 2026 |

## Paper authors

- [Manuel J. Pérez-Salazar](https://scholariq.org/researchers/manuel-j-perez-salazar/)

## Paper journal

- [Lecture notes in computer science](https://scholariq.org/journals/lecture-notes-in-computer-science/)

## Paper primary topic

- [Surgical Simulation and Training](https://scholariq.org/topics/surgical-simulation-and-training/)

## Paper topics

- [Surgical Simulation and Training](https://scholariq.org/topics/surgical-simulation-and-training/)
- [Non-Invasive Vital Sign Monitoring](https://scholariq.org/topics/non-invasive-vital-sign-monitoring/)
- [Intraoperative Neuromonitoring and Anesthetic Effects](https://scholariq.org/topics/intraoperative-neuromonitoring-and-anesthetic-effects/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.