Fatigue and respiratory disorders

Wearable biosensors for human fatigue diagnosis: A review

Fatigue causes deleterious effects to physical and mental health of human being and may cause loss of lives. Therefore, the adverse effects of fatigue on individuals and the society are massive. With the ever-increasing frequency of overtraining among modern military and sports personnel, timely, portable and accurate fatigue diagnosis is essential to avoid fatigue-induced accidents. However, traditional detection methods require complex sample preparation and blood sampling processes, which cannot meet the timeliness and portability of fatigue diagnosis. With the development of flexible materials and biosensing technology, wearable biosensors have attracted increased attention to the researchers. Wearable biosensors collect biomarkers from noninvasive biofluids, such as sweat, saliva, and tears, followed by biosensing with the help of biosensing modules continuously and quantitatively. The detection signal can then be transmitted through wireless communication modules that constitute a method for real-time understanding of abnormality. Recent developments of wearable biosensors are focused on miniaturized wearable electrochemistry and optical biosensors for metabolites detection, of which, few have exhibited satisfactory results in medical diagnosis. However, detection performance limits the wide-range applicability of wearable fatigue diagnosis. In this article, the application of wearable biosensors in fatigue diagnosis has been discussed. In fact, exploration of the composition of different biofluids and their potential toward fatigue diagnosis have been discussed here for the very first time. Moreover, discussions regarding the current bottlenecks in wearable fatigue biosensors and the latest advancements in biochemical reaction and data communication modules have been incorporated herein. Finally, the main challenges and opportunities were discussed for wearable fatigue diagnosis in the future.

Evaluation of psychological and physiological predictors of fatigue in patients with COPD

BACKGROUND

Fatigue in COPD impairs functional status; however there are few studies examining mechanistic pathways of this symptom. The aims of this study are to compare fatigue between COPD patients and healthy age-matched subjects, and to identify predictors of fatigue in COPD.

METHODS

Seventy four COPD patients, mean age 69.9 (49-87) yrs, mean (SD) % predicted FEV1 46.5 (20.0) % and FEV1/FVC ratio 0.45 (0.13) and 35 healthy subjects, mean age 67.1 (50-84) yrs completed the Multidimensional Fatigue Inventory (MFI 20). Patients' assessment included Depression (HADS), lung function, BMI, muscle strength, incremental shuttle walk test (ISWT), exercise oxygen saturation (SpO2), Borg breathlessness (CR-10) and exertion (RPE). Serum level of Interleukin 6 (IL-6) was recorded. Differences in MFI 20 between groups were examined and predictors of fatigue identified using logistic regression.

RESULTS

Significant differences (p < 0.01) were found between the COPD and healthy subjects for all MFI 20 dimensions. There were significant differences when classified according to GOLD and dyspnoea stages for selected dimensions only. Predictors of General Fatigue were depression, muscle strength and end SpO2 (R2 = .62); of Physical Fatigue: depression, % predicted FEV1, ISWT and age (R2 = .57); Reduced Activity: % predicted FEV1, BMI and depression (R2 = .36); Reduced Motivation: RPE, depression and end SpO2 (R2 = .37) and Mental Fatigue: depression and end SpO2 (R2 = .38).

CONCLUSION

All dimensions of fatigue were higher in COPD than healthy aged subjects. Predictive factors differ according to the dimension of fatigue under investigation. COPD-RF is a multi component symptom requiring further consideration.