Monitoring of motor symptom fluctuations in Parkinson’s disease (PD) patients is currently performed through the subjective self-assessment of patients. Clinicians require reliable information about a fluctuation’s occurrence to enable a precise treatment rescheduling and dosing adjustment. In this review, we analyzed the utilization of sensors for identifying motor fluctuations in PD patients and the application of machine learning techniques to detect fluctuations. The review process followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Ten studies were included between January 2010 and March 2021, and their main characteristics and results were assessed and documented. Five studies utilized daily activities to collect the data, four used concrete scenarios executing specific activities to gather the data, and only one utilized a combination of both situations. The accuracy for classification was 83.56–96.77%. In the studies evaluated, it was not possible to find a standard cleaning protocol for the signal captured, and there is significant heterogeneity in the models utilized and in the different features introduced in the models (using spatiotemporal characteristics, frequential characteristics, or both). The two most influential factors in the good performance of the classification problem are the type of features utilized and the type of model.

In various regions of the world, there is great concern about existing gender differences, which could affect opportunities for economic growth, and how to mitigate them. Entrepreneurship is of great importance to the economy and in a global society, and it is a hot topic for interested public decision makers due to its growing importance in economic activity—as it creates jobs, increases competitiveness and modernizes the economy. Sustainability is also a critical topic when designing the future economy, and combining female entrepreneurship with sustainability results in a very interesting topic to be evaluated when pursuing sustainable development. This paper tries to shed light on the relationship between female entrepreneurship and sustainability by analyzing 28 different papers from the Web of Science (WoS) database. Its main conclusion supports the idea that awareness of women is relevant to sustainability when starting a new company. However, further research is required due to the novelty of the topic and also the existing gaps in knowledge.

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Entrepreneurship is a key activity in the economy as it influences in the economic performance by creating new products, new solutions, new methods, new processes and new jobs. High levels entrepreneurship in economies have a positive impact on productivity and competitiveness. According to data from Eurostat (2018), in 2018 in Europe, 3.3 million jobs were created thanks to the 2.5 million companies that were created. Moreover, in 2018, there were a total of 25.3 million active enterprises employing a total of 131 million people. Some of the most relevant entrepreneurial hotpots in Europe are Estonia, Sweden, Latvia and the Netherlands (World Economic Forum, 2017). The main objective of this work is to identify and compare the different European geographical areas and evaluate the characteristics and variables that promote entrepreneurship from the experts' point of view. The GEM database was utilized to extract data for analysis in this research. The results obtained show differences between the Northern and Southern countries for the two analysis perspectives used.