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An electronic device, a system, and a method for determining a suitable workout in consideration of a context are provided. The electronic device includes a communication module comprising communication circuitry configured to communicate with at least one other electronic device; a display configured to provide a user interface; a memory configured to store instructions therein; and a processor electrically connected to the communication module, the display, and the instructions stored in the memory, when executed by the processor, cause the processor to receive a command for executing a workout program, to collect context data for a user, and to determine whether it is suitable for the user to perform planned workout content based on the collected context data. This application is based on and claims priority under 35 U. The present disclosure relates generally to an electronic device, a system, and a method for determining a suitable workout in consideration of a context. For example, the present disclosure relates to an electronic device, a system, and a method for providing a suitable workout to a user using various contexts related to the user. Recently, as people are increasingly concerned about healthcare and fitness, various devices for more scientific workout and body health care, in particular, for weight loss treatments, have been provided. For example, wearable devices that can be conveniently worn on the body to measure an exercise amount for exercise treatments have been provided. A wearable device may refer, for example, to a device that can be attached to a user's body to perform a computing action. For example, a wearable device may be implemented in various types that can be attached to the user's body, such as, a watch, glasses, a bracelet, a ring, a necklace, shoes, and a sticker.

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The human body is a complex electro-mechanical system that generates electrical, mechanical, thermal, and other signals that we normally call Biomedical Signals. The automatic analysis of biomedical signals has become an important process to both identify indicators of diseased states and to provide meaningful information for various applications in physiology, sports medicine and human—computer interface. Recent advances in Artificial Intelligence AI have the potential to manage and analyze large biomedical datasets leading to the clinical Spectral Analysis On Photoplethysmogram Ppg and real-time applications. These techniques have been applied successfully to medical imaging, but the analysis of 1D biomedical signals has yet to fully benefit from this novel approach. Biomedical Signal and Image Processing includes the analysis, classification, and manipulation of signals by means of operations like filtering, compression, feature extraction, enhancement and spectral analysis.

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Under such conditions, the use of computational innovative techniques based on the convergence of signal and image processing will help us to get new solutions to the real-world challenges. This Special Issue is aimed at sharing the innovative ideas and algorithms in the Biomedical Signal and Image Processing domain. Precisely, the objective of this Special Issue is to focus attention on emerging methods and techniques based Anxlysis the transformation of biomedical signals into images and their processing through AI-based image processing approaches.

With this mission, the principal aim of this Special Issue is to collect original contributions as either research papers or comprehensive reviews that address and discuss the impact and relevance of signals and images processing in research Photoplethyxmogram applicative areas such as:. Alfred M. Bruckstein — Dep. All Rights Reserved.

Maintained by Imed. Biomedical Signal Processing and Control.]