Assessing stability and accuracy of a novel commercial wearable near-infrared spectroscopy device

The article discusses the use of Near-infrared spectroscopy (NIRS) to measure muscle oxygenation levels in athletes to optimize their training performance. A new NIRS sensor called Train.Red FYER was developed for this purpose. The stability, accuracy, intra- and inter-variability of muscle oxygenation saturation (SmO2) were assessed using two different phantoms and in-vivo tests. The sensor was found to be stable and precise, with inter-variability being larger than intra-variability. The article concludes that the new NIRS sensor can be used to measure SmO2 accurately in athletes during endurance and strength activities.

Application of a recurrent neural network to predict the oxygenated recovery state following maximum isometric hand gripping exercise

The article discusses using Near-InfraRed Spectroscopy (NIRS) to study rest periods between strength exercises and develop a model for predicting the oxygenated recovery state. A Recurrent Neural Network (RNN) was trained to predict shifts between the four manually categorized phases of recovery. The RNN and Multi-Layer Perceptron (MLP) had similar accuracy, but the RNN was more consistent. This can help athletes design more efficient training programs.

Train.Red shines a light on your performance based on light technology, the FYER looks inside your muscles with Near InfraRed Spectroscopy (NIRS). The sensor translates the oxygen saturation and (de-)oxyhemoglobin changes in your muscle tissue ixnto real-time key features with the help of artificial intelligence and a friendly user interface.

Our partner Artinis Medical Systems has over 1500 publications.