Purpose: Online adaptive correction in image-guided intensity-modulated radiotherapy appears to be a promising approach for precision radiation treatment in head-and-neck tumors. This research is designed to evaluate the setup uncertainties in the left-right (L-R), superior-inferior (S-I), and anterior-posterior (A-P) directions and rotational variations: pitch, roll, and yaw for head-and-neck cancer (HNC) patients with the ExacTrac 6 degree-of-freedom (6D) image-guided radiotherapy (IGRT) system. Materials and Methods: The setup errors measured by ExacTrac 6D IGRT system at the treatment unit with respect to the planning computed tomography were recorded for 40 patients with head-and-neck tumors. The residual setup errors were computed and quantitatively analyzed. Results: The results indicated that the setup errors measured in the S-I direction were larger than the other two directions. For the three rotational angles, the results were very close. The verifications showed that after the first correction, the overall setup errors were generally <0.32 mm in the L-R, S-I, and A-P directions and <0.2° in the three rotational variations: pitch, roll, and yaw. According to the results of verifications, we know that ExacTrac 6D IGRT system was accurate and clinical feasibility. Conclusion: The results of our study have shown that daily image guidance with ExacTrac 6D image-guided system for HNC patients is effective. These data suggest it allows a high accurate of setup errors.

Background and Objective: Portable and readily accessible wellness devices can aid vital sign measuring for those interested in tracking their health. In this diagnostic accuracy study, we evaluated the performance of the VitalWellness device (VW), a wireless, compact, noninvasive device that measures four vital signs (VS) – blood pressure (BP), heart rate (HR), respiratory rate (RR), and body temperature (BT) – using the index finger and forehead. Methods: Adult volunteers with VS that fell both within and outside of the normal physiological range were enrolled to provide BP, HR, RR, and BT measurements using both the VW and Food and Drug Administration-approved reference devices. A subgroup of participants underwent an additional test to analyze the VW's performance on HR and RR outside of normal physiological ranges. Statistical measurements were plotted on scatter and Bland–Altman plots. Sensitivity analyses to evaluate the VW's performance by gender, skin color, finger size, and auxiliary activities were performed. Results: A total of 263 participants completed the study. On an average, systolic BP measured using the VW was 10 mmHg lower than that of the reference device (correlation coefficient r = 0.7), whereas diastolic BP was 3 mmHg lower (r = 0.6), and RR was 2 bpm lower (r = 0.7). VW HR and BT measurements were, on average, 1 bpm and 0.3°F higher than the corresponding reference measurements (r = 0.9 and r = 0.3), respectively. Conclusion: The VW device is well-suited for home-based, nonmedical monitoring of HR, RR, and BP. Further improvement in measurement accuracy is required to enable applications for medical use.

Psychophysiological decompensation as a result of occupational stress leads to impairment of occupational performance. Adequate recovery from psychological stress is necessary to maintain occupational performance. It is possible to measure the psychophysiological status and recovery during sleep with health data streamed from biomedical digital devices. Such data, with reference to heart and sleep parameters, could be processed to reflect health status and whether there is a risk of psychophysiological decompensation. This article describes the interpretation of resting heart rate measures, heart rate variability, and actigraphy measures during regular sleep in relation to psychological stress. Interpretation of the health data should be done by informed health-care professionals in combination with clinical history taking. The article does not cover digital measurements while awake and active. The aim of this review article is to provide an evidence-based rationale to health professionals how to interpret digital health data profiles from biomedical devices in appraising psychological stress and recovery. The objective is to prevent the adverse impact of psychological stress on health. Specific lifestyle measures and therapy to manage psychological stress, such as exercise, diet, and cognitive behavioral therapy for insomnia, are not discussed in this article. Applications are especially relevant in the field of occupational health in preventing occupational burnout, achieving a healthy work–life balance, and sustaining a healthy working life. There are future implications with regard to disease prevention as a large proportion of chronic diseases, for example, hypertension, diabetes depression, and ischemic heart disease, are related to chronic psychological stress. Stress monitoring with biomedical devices should occur over periods of work and nonwork days.