Mental fatigue, characterized by subjective feelings of "tiredness" and "lack of energy", can degrade individual performance in a variety of situations, for example, in motor vehicle driving or while performing surgery. Thus, a method for nonintrusive monitoring of mental fatigue status is urgently needed. Recent research shows that physiological signal-based fatigueclassification methods using wearable electronics can be sufficiently accurate; by contrast, rigid, bulky devices constrain the behavior of those wearing them, potentially interfering with test signals. Recently, wearable electronics, such as epidermal electronics systems (EES) and electronic tattoos (E-tattoos), have been developed to meet the requirements for the comfortable measurement of various physiological signals. However, comfortable, effective, and nonintrusive monitoring of mental fatigue levels remains to be fulfilled. In this work, an EES is established to simultaneously detect multiple physiological signals in a comfortable and nonintrusive way. Machine-learning algorithms are employed to determine the mental fatigue levels and a predictive accuracy of up to 89% is achieved based on six different kinds of physiological features using decision tree algorithms. Furthermore, EES with the trained predictive model are applied to monitor in situ human mental fatigue levels when doing several routine research jobs, as well as the effect of relaxation methods in relieving fatigue.

Background:Currently available evaluation criteria for penile tumescence and rigidity have been fraught with controversy. In this study, we sought to establish normative Chinese evaluation criteria for penile tumescence and rigidity by utilizing audiovisual sexual stimulation and RigiScan™ test (AVSS-Rigiscan test) with the administration of phosphodiesterase-5 inhibitor.Methods:A total of 1169 patients (aged 18–67 years) complained of erectile dysfunction (ED) underwent AVSS-RigiScan test with the administration of phosphodiesterase-5 inhibitor. A total of 1078 patients whose final etiological diagnosis was accurate by means of history, endocrine, vascular, and neurological diagnosis, International Index of Erectile Function 5 questionnaire, and erection hardness score were included in the research. Logistic regression model and receiver operating characteristic curve analysis were performed to determine the cutoff value of the RigiScan™ data. Then, the multivariable logistic analysis was used in the selected variables.Results:A normal result is defined as one erection with basal rigidity over 60% sustained for at least 8.75 min, average event rigidity of tip at least 43.5% and base at least 50.5%, average maximum rigidity of tip at least 62.5% and base at least 67.5%, △tumescence (increase of tumescence or maximum−minimum tumescence) of tip at least 1.75 cm and base at least 1.95 cm, total tumescence time at least 29.75 min, and times of total tumescence at least once. Most importantly, basal rigidity over 60% sustained for at least 8.75 min, average event rigidity of tip at least 43.5%, and base at least 50.5% would be the new normative Chinese evaluation criteria for penile tumescence and rigidity. By multivariable logistic regression analysis, six significant RigiScan™ parameters including times of total tumescence, duration of erectile episodes over 60%, average event rigidity of tip, △tumescence of tip, average event rigidity of base, and △tumescence of base contribute to the risk model of ED. In logistic regression equation, predict value P < 0.303 was considered as psychogenic ED. The sensitivity and specificity of the AVSS-RigiScan test with the administration of phosphodiesterase-5 inhibitor in discriminating psychogenic from organic ED was 87.7% and 93.4%, respectively.Conclusions:This study suggests that AVSS-RigiScan test with oral phosphodiesterase-5 inhibitors can objectively assess penile tumescence and rigidity and seems to be a better modality in differentiating psychogenic from organic ED. However, due to the limited sample size, bias cannot be totally excluded.

No abstract