Chronic subjective tinnitus is the constant perception of a sound that has no physical source. Brain imaging studies show alterations in tinnitus patients’ resting-state networks (RSNs). This scoping review aims to provide an overview of resting-state fMRI studies in tinnitus, and to evaluate the evidence for changes in different RSNs. A total of 29 studies were included, 26 of which found alterations in networks such as the auditory network, default mode network, attention networks, and visual network; however, there is a lack of reproducibility in the field which can be attributed to the use of different regions of interest and analytical methods per study, and tinnitus heterogeneity. Future studies should focus on replication by using the same regions of interest in their analysis of resting-state data, and by controlling adequately for potential confounds. These efforts could potentially lead to the identification of a biomarker for tinnitus in the future.

As the financial cost of electronics is constantly decreasing and new electronic modules are being introduced to the market, the development of many healthcare applications becomes easier, cheaper and more prospects are created for various healthcare related fields. Some of these fields are the pre-hospital care and the telemedicine, which have a lot to contribute to modern healthcare provision. The purpose of this paper is to present the development of an electronic biomedical device that will measure and send a number of biosignals, while at the same time being lightweight enough to be transferred by an unmanned air vehicle to achieve a better pre-hospital service in case of urgent care situations. The system was built trying to keep the total cost on a low level. Finally, some measurements were taken to check the device’s proper functionality and conclusions were drawn.

It has been shown that monitoring temporary threshold shift (TTS) after exposure to noise may have a predictive value for susceptibility of developing permanent noise-induced hearing loss. The aim of this study is to present the assumptions of the TTS predictive model after its verification in normal hearing subjects along with demonstrating the usage of this model for the purposes of public health policy. Material and Methods:The existing computational predictive TTS models were adapted and validated in a group of 18 bartenders exposed to noise at the workplace. The performance of adapted TTS predictive model was assessed by receiver operating characteristic (ROC) analysis. The demonstration example of the usage of this model for estimating the risk of TTS in general unscreened population after exposure to loud music in discotheque bars or music clubs is provided. Results: The adapted TTS predictive model shows a satisfactory agreement in distributions of actual and predicted TTS values and good correlations between these values in examined bartenders measured at 4 kHz, and as a mean at speech frequencies (0.5-4 kHz). An optimal cut-off level for recognizing the TTS events, ca. 75% of young people (aged ca. 35 years) may experience TTS >5 dB, while <10% may exhibit Funding: this study was supported by European Union's Horizon 2020 research and innovation program (project No. 727521 entitled "EVOTION" EVidenced based management of hearing impairments: Public health pΟlicy making based on fusing big data analytics and simulaTION, " grant/project manager: Niels Hendrik Pontoppidan) and by Ministry of Science and Higher Education of Poland (project No. 18.21/2020-2021 entitled "Development of a predictive model for estimating the temporal shift of the hearing threshold after exposure to noise for the prevention of occupational hearing impairment, " project manager: Mariola Śliwińska-Kowalska).

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