A framework for comparative study of databases and computational methods for arrhythmia detection from single-lead ECG.

Arrhythmia detection from ECG is an important area of computational ECG analysis. However, although a large number of public ECG recordings are available, most research uses only few datasets, making it difficult to estimate the generalizability of the plethora of ECG classification methods. Furthermore, there is a large variability in the evaluation procedures, as well as lack of insight into whether they could successfully perform in a real-world setup.

Power Autonomy Estimation of Low-Power Sensor for Long-Term ECG Monitoring.

The paper analyses the autonomy of a wireless body sensor that continuously measures the potential difference between two proximal electrodes on the skin, primarily used for measuring an electrocardiogram (ECG) when worn on the torso. The sensor is powered by a small rechargeable battery and is designed for extremely low power use. However, the autonomy of the sensor, regarding its power consumption, depends significantly on the measurement quality selection, which directly influences the amount of data transferred.

Patient-Specific Heartbeat Classification in Single-Lead ECG using Convolutional Neural Network.

For an expert cardiologist, any abnormality in the heart rhythm or electrocardiogram (ECG) shape can be easily detected as a sign of arrhythmia. However, this is a big challenge for a computer system. The need for automatic arrhythmia recognition comes from the development of many portable ECG measuring devices designed to function as a part of health monitoring platforms.

Framework for Personalized Real-Time Control of Hidden Temperature Variables in Therapeutic Knee Cooling.

The paper formalizes, implements and evaluates a framework for personalized real-time control of inner knee temperature during cryotherapy after knee surgery. Studies have shown that the cryotherapy should be controlled depending on the individual patient's feedback on the cooling, which raises the need for smart personalized therapy. The framework is based on the feedback control loop that uses predicted instead of measured inner temperatures because measurements are not feasible or would introduce invasiveness into the system.

Medical-Grade ECG Sensor for Long-Term Monitoring.

The recent trend in electrocardiogram (ECG) device development is towards wireless body sensors applied for patient monitoring. The ultimate goal is to develop a multi-functional body sensor that will provide synchronized vital bio-signs of the monitored user. In this paper, we present an ECG sensor for long-term monitoring, which measures the surface potential difference between proximal electrodes near the heart, called differential ECG lead or differential lead, in short.

Non-invasive real-time prediction of inner knee temperatures during therapeutic cooling.

The paper addresses the issue of non-invasive real-time prediction of hidden inner body temperature variables during therapeutic cooling or heating and proposes a solution that uses computer simulations and machine learning. The proposed approach is applied on a real-world problem in the domain of biomedicine - prediction of inner knee temperatures during therapeutic cooling (cryotherapy) after anterior cruciate ligament (ACL) reconstructive surgery. A validated simulation model of the cryotherapeutic treatment is used to generate a substantial amount of diverse data from different simulation scenarios.

Knee temperatures measured in vivo after arthroscopic ACL reconstruction followed by cryotherapy with gel-packs or computer controlled heat extraction.

Purpose: To obtain in vivo data about intra- and extra-articular knee temperatures to assess the effectiveness of two cryotherapeutic methods-conventional cooling with gel-packs and computer controlled cryotherapy following anterior cruciate ligament (ACL) reconstructive surgery.

Methods: Twenty patients were arbitrarily assigned for cryotherapy after ACL reconstruction: 8 patients with frozen gel-packs and 12 patients with computer controlled cryotherapy with constant temperatures of the cooling liquid in the knee pads. The treatment was performed for 12 h.

Two proximal skin electrodes--a respiration rate body sensor.

We propose a new body sensor for extracting the respiration rate based on the amplitude changes in the body surface potential differences between two proximal body electrodes. The sensor could be designed as a plaster-like reusable unit that can be easily fixed onto the surface of the body. It could be equipped either with a sufficiently large memory for storing the measured data or with a low-power radio system that can transmit the measured data to a gateway for further processing.