Title :
Mobile Crowd Sensing in Clinical and Psychological Trials -- A Case Study
Author :
Pryss, Rudiger ; Reichert, Manfred ; Herrmann, Jochen ; Langguth, Berthold ; Schlee, Winfried
Author_Institution :
Inst. of Databases & Inf. Syst., Ulm Univ., Ulm, Germany
Abstract :
Many highly prevalent diseases (e.g., tinnitus, migraine, chronic pain) are difficult to treat and universally effective treatments are missing. Available treatments are only effective in patient subgroups, i.e., medical doctors and patients have to figure out which therapy might be helpful in the patient´s situation. Sufficiently large and qualitative longitudinal data sets, however, would be desirable to facilitate evidence-based treatment decisions for individual patients. On one hand, traditional sensing techniques (i.e., clinical trials) have many merits enabling evidence-based medicine. On the other, they have inherent limitations. First, clinical trials are very cost- and labour-intensive. Second, the traditional approach aims at reducing ecological heterogeneity to enable the investigation of homogeneous subsamples. Recently, a new paradigm emerged that offers promising perspectives for collecting large amounts of longitudinal patient data -- Mobile Crowd Sensing. By utilizing smart mobile devices of a large number of patients, health information can be gathered from large patient collections as well as at many different time points and in various real life environmental situations. In the Track Your Tinnitus project, we implemented such a mobile crowd sensing platform to reveal new medical aspects about tinnitus with a particular focus on the variability of tinnitus over time depending on the environmental situation. In this paper, the current project status as well as first lessons learned from running the mobile application for twelve months are presented. In turn, the lessons learned are discussed in the context of the new perspectives offered by mobile crowd sensing in the medical field.
Keywords :
biomedical communication; biomedical measurement; diseases; health care; medical computing; mobile computing; patient treatment; psychology; smart phones; Track Your Tinnitus project; clinical trials; diseases; ecological heterogeneity; evidence-based medicine; evidence-based treatment decisions; health information; homogeneous subsamples; large longitudinal data sets; medical field; mobile application; mobile crowd sensing platform; patient subgroups; psychological trials; qualitative longitudinal data sets; real life environmental situations; smart mobile devices; time 12 month; time points; tinnitus; traditional sensing techniques; universally effective treatments; Clinical trials; Mobile communication; Mobile handsets; Psychology; Sensors; clinical trial; mobile crowd sensing; mobile healthcare application; psychological trial; tinnitus; tinnitus variablity;
Conference_Titel :
Computer-Based Medical Systems (CBMS), 2015 IEEE 28th International Symposium on
Conference_Location :
Sao Carlos
DOI :
10.1109/CBMS.2015.26