Biomedical Signal Processing and Control

The Journal of Biomedical Signal Processing and Control (BSPC), the Official Journal of the European Alliance of Medical and Biological Engineering and Science (EAMBES), publishes original, high-quality research that advances the theory, methodology, and application of signal and data processing techniques for understanding, modelling, and improving human health. The journal provides an interdisciplinary platform at the intersection of engineering, data science, and medicine, with a focus on extracting meaningful physiological, pathological, and behavioural information from biomedical signals, images, and related data.

BSPC welcomes contributions that develop novel methods for signal and image acquisition, processing, analysis, modelling, and interpretation, as well as clinically validated applications. Emphasis is placed on approaches that address real-world challenges such as noise, non-stationarity, high dimensionality, multimodality, personalization, real-time operation, and interpretability, and that demonstrate clear translational relevance to healthcare, diagnostics, therapeutics, rehabilitation, and biomedical research.

A defining characteristic of BSPC is its emphasis not only on the analysis of biomedical signals and medical images, but also on how these data are used to drive decisions, feedback mechanisms, and closed-loop control in medical devices, digital health technologies, and clinical systems.

Scope of the Journal

The scope includes—but is not limited to—the following topics:

• Processing and analysis of biomedical signals such as EEG, ECG, EMG, EOG, MEG, PPG, respiratory signals, blood pressure, neural recordings, and biosensor data

• Medical image processing and analysis, and integration of imaging with physiological signals

• Multimodal and multiscale signal processing and data fusion

• Machine learning, deep learning, and statistical methods for biomedical signal and image analysis

• Time–frequency, adaptive, nonlinear, and data-driven signal processing methods

• Brain–computer interfaces, neurotechnology, and neurophysiological systems

• Wearable, implantable, mobile, and remote health monitoring systems

• Physiological modelling, digital biomarkers, and data-driven health analytics

• Signal quality assessment, artifact detection, denoising, and robustness analysis

• Personalized and precision medicine enabled by signal and data analytics

• Real-time systems, embedded implementations, and clinical or translational validation

• Closed-loop and feedback-controlled biomedical systems, including therapeutic and assistive devices

The journal encourages submissions ranging from theoretical advances and algorithmic innovations to experimental studies, clinical investigations, prototype systems, and benchmark or dataset papers. By fostering collaboration across disciplines, Biomedical Signal Processing and Control aims to accelerate the development of robust, interpretable, and clinically impactful signal- and data-driven solutions for modern healthcare.