Background In medicine, the symptom of dizziness is one of the most common multidisciplinary causes of emergency medical presentation. Attending physicians are often faced with difficult decisions when evaluating patients with dizziness. A rapid differential diagnostic decision must be made during the initial examination. The goal of this study, was to develop a smartphone-based app that can diagnose and qualify nystagmus. The app should enable differentiation between acute emergencies such as strokes ("central vertigo") and vestibular disorders ("peripheral vertigo") using and recognizing or analyzing the accompanying symptom "nystagmus". Materials and methods This prospective study was conducted at the Department of Otolaryngology, Head and Neck Surgery "Otto Körner", Rostock (Germany). The experimental study design consisted of two test runs and two control runs. In the two test runs, nystagmus was tracked and evaluated by caloric and optokinetic stimulation, respectively, through a custom-developed app. Sensitivity and correlation were calculated for the app's application performance and compared under different experimental conditions. Results The patient sample included twenty healthy participants with a mean age of 25.6 years (± 2.2 SD) who participated in the study. The overall sensitivity of detection of nystagmus averaged 82.14% in the optokinetic stimulation test trials. There is no correlation regarding specific subject data and sensitivity. Conclusions The results of our experimental validation study show that a smartphone-based nystagmus app is a useful tool for vertigo diagnosis. The results of our analyses show that it is possible to diagnose nystagmus and determine shape or direction with the app.

This paper describes a telemonitoring system that allows the examination of preventive-medicine subjects in daily routines. The system combines the acquisition of different physiological data and the subjective workload of the subjects. A mobile handheld/smart phone depicts the data node of the afield system part and organises the data flow of the sensor system and integrated questionnaires. It continuously transfers the data to a central process management system, which stores the data in a database and executes the real-time data processing via different modules. The modules contain different regression and fuzzy models for an individual analysis of the data. All results are also stored by the process manager and the important results are sent to a medical information management system to provide examiners and subjects with the data. The developed system reduces the effort for the examiner and increases the quality of research studies significantly. Moreover, concerning the direct supply of raw and processed data during and after the examination, the system is timesaving with regard to the examiners.