Classification of retinal vessels using a collaborative agent-based architecture

BeSafe B2.0 Smart Multisensory Platform for Safety in Workplaces

Wearable technologies are becoming a profitable means of monitoring a person’s health state, such as heart rate and physical activity. The use of the smartwatch is becoming consolidated, not only as a novelty but also as a very useful tool for daily use. In addition, other devices, such as helmets or belts, are beneficial for monitoring workers and the early detection of any anomaly. They can provide valuable information, especially in work environments, where they help reduce the rate of accidents and occupational diseases, which makes them powerful Personal Protective Equipment (PPE). The constant monitoring of the worker’s health can be done in real-time, through temperature, falls, noise, impacts, or heart rate meters, activating an audible and vibrating alarm when an anomaly is detected. The gathered information is transmitted to a server in charge of collecting and processing it. In the first place, this paper provides an exhaustive review of the state of the art on works related to electronics for human activity behavior. After that, a smart multisensory bracelet, combined with other devices, developed a control platform that can improve operators’ security in the working environment. Artificial Intelligence and the Internet of Things (AIoT) bring together the information to improve safety on construction sites, power stations, power lines, etc. Real-time and historic data is used to monitor operators’ health and a hybrid system between Gaussian Mixture Model and Human Activity Classification. That is, our contribution is also founded on the use of two machine learning models, one based on unsupervised learning and the other one supervised. Where the GMM gave us a performance of 80%, 85%, 70%, and 80% for the 4 classes classified in real time, the LSTM obtained a result under the confusion matrix of 0.769, 0.892, and 0.921 for the carrying-displacing, falls, and walking-standing activities, respectively. This information was sent in real time through the platform that has been used to analyze and process the data in an alarm system.

Automatic image analyser to assess retinal vessel calibre (ALTAIR). A new tool to evaluate the thickness, area and length of the vessels of the retina

BACKGROUND AND OBJECTIVES

The examination of the fundus allows to evaluate retinal the microcirculation in vivo. We assess the reliability and validity of ALTAIR software, and to evaluate its clinical relevance by the association of thickness, area and length of the retinal vessels with other measures of vascular structure and function, target organ damage and cardiovascular risk.

METHODS

Cross-sectional study involving a total of 250 subjects aged 62 ± 9 years, 51 % males. In a random subsample of 60 subjects (118 retinographies), we estimated the intraobserver, interobserver and interdevice intraclass correlation coefficients (ICC) of the measurements of retinal vascular thickness, area and length in 3 concentric circles. Concurrent validity was assessed with all 250 subjects (495 retinographies), analysing the relationship to age, blood pressure, target organ damage, vascular structure and function, and cardiovascular risk.

RESULTS

Of the sample, 69 % were diagnosed with hypertension and 17 % with diabetes. Intraobserver ICC ranged from 0.640 for venous length to 0.906 for arterial area. Interobserver ICC ranged from 0.809 for arterial length to 0.916 for venous area, and interdevice ICC for arteriovenous ratio (AVR) was 0.887, thickness of arteries 0.590 and vein thickness 0.677. We found a moderate correlation between retinal vascular parameters and vascular structure and function, and target organ damage. In multiple linear regression analysis, the association with blood pressure, albumin/creatinine ratio, carotid intima-media thickness and cardiovascular risk is maintained.

CONCLUSION

The ALTAIR tool has been useful for analysing the thickness, area and length of retinal vessels, with adequate reliability and a concomitant association of retinal vessel measurements with other cardiovascular parameters and cardiovascular risk. Therefore, in addition to thickness, the area and length of retinal vessels could also play a role in the prediction of cardiovascular risk.