Detecting Psychological Interventions Using Bilateral Electromyographic Wearable Sensors.

This study investigated the impact of auditory stimuli on muscular activation patterns using wearable surface electromyography (EMG) sensors. Employing four key muscles (Sternocleidomastoid Muscle (SCM), Cervical Erector Muscle (CEM), Quadricep Muscles (QMs), and Tibialis Muscle (TM)) and time domain features, we differentiated the effects of four interventions: silence, music, positive reinforcement, and negative reinforcement. The results demonstrated distinct muscle responses to the interventions, with the SCM and CEM being the most sensitive to changes and the TM being the most active and stimulus dependent. Post hoc analyses revealed significant intervention-specific activations in the CEM and TM for specific time points and intervention pairs, suggesting dynamic modulation and time-dependent integration. Multi-feature analysis identified both statistical and Hjorth features as potent discriminators, reflecting diverse adaptations in muscle recruitment, activation intensity, control, and signal dynamics. These features hold promise as potential biomarkers for monitoring muscle function in various clinical and research applications. Finally, muscle-specific Random Forest classification achieved the highest accuracy and Area Under the ROC Curve for the TM, indicating its potential for differentiating interventions with high precision. This study paves the way for personalized neuroadaptive interventions in rehabilitation, sports science, ergonomics, and healthcare by exploiting the diverse and dynamic landscape of muscle responses to auditory stimuli.

Identifying Current Feelings of Mild and Moderate to High Depression in Young, Healthy Individuals Using Gait and Balance: An Exploratory Study.

Depressive mood states in healthy populations are prevalent but often under-reported. Biases exist in self-reporting of depression in otherwise healthy individuals. Gait and balance control can serve as objective markers for identifying those individuals, particularly in real-world settings. We utilized inertial measurement units (IMU) to measure gait and balance control. An exploratory, cross-sectional design was used to compare individuals who reported feeling depressed at the moment (n = 49) with those who did not (n = 84). The Quality Assessment Tool for Observational Cohort and Cross-sectional Studies was employed to ensure internal validity. We recruited 133 participants aged between 18-36 years from the university community. Various instruments were used to evaluate participants' present depressive symptoms, sleep, gait, and balance. Gait and balance variables were used to detect depression, and participants were categorized into three groups: not depressed, mild depression, and moderate-high depression. Participant characteristics were analyzed using ANOVA and Kruskal-Wallis tests, and no significant differences were found in age, height, weight, BMI, and prior night's sleep between the three groups. Classification models were utilized for depression detection. The most accurate model incorporated both gait and balance variables, yielding an accuracy rate of 84.91% for identifying individuals with moderate-high depression compared to non-depressed individuals.

Modeling Cues May Reduce Sway Following Sit-To-Stand Transfer for People with Parkinson's Disease.

Cues are commonly used to overcome the effects of motor symptoms associated with Parkinson's disease. Little is known about the impact of cues on postural sway during transfers. The objective of this study was to identify if three different types of explicit cues provided during transfers of people with Parkinson's disease results in postural sway more similar to healthy controls. This crossover study had 13 subjects in both the Parkinson's and healthy control groups. All subjects completed three trials of uncued sit to stand transfers. The Parkinson's group additionally completed three trials of sit to stand transfers in three conditions: external attentional focus of reaching to targets, external attentional focus of concurrent modeling, and explicit cue for internal attentional focus. Body worn sensors collected sway data, which was compared between groups with Mann Whitney U tests and between conditions with Friedman's Tests. Sway normalized with modeling but was unchanged in the other conditions. Losses of balance presented with reaching towards targets and cueing for an internal attentional focus. Modeling during sit to stand of people with Parkinson's disease may safely reduce sway more than other common cues.

Identifying Individuals Who Currently Report Feelings of Anxiety Using Walking Gait and Quiet Balance: An Exploratory Study Using Machine Learning.

Literature suggests that anxiety affects gait and balance among young adults. However, previous studies using machine learning (ML) have only used gait to identify individuals who report feeling anxious. Therefore, the purpose of this study was to identify individuals who report feeling anxious at that time using a combination of gait and quiet balance ML. Using a cross-sectional design, participants (n = 88) completed the Profile of Mood Survey-Short Form (POMS-SF) to measure current feelings of anxiety and were then asked to complete a modified Clinical Test for Sensory Interaction in Balance (mCTSIB) and a two-minute walk around a 6 m track while wearing nine APDM mobility sensors. Results from our study finds that Random Forest classifiers had the highest median accuracy rate (75%) and the five top features for identifying anxious individuals were all gait parameters (turn angles, variance in neck, lumbar rotation, lumbar movement in the sagittal plane, and arm movement). Post-hoc analyses suggest that individuals who reported feeling anxious also walked using gait patterns most similar to older individuals who are fearful of falling. Additionally, we find that individuals who are anxious also had less postural stability when they had visual input; however, these individuals had less movement during postural sway when visual input was removed.

Association between Self-Reported Prior Night's Sleep and Single-Task Gait in Healthy, Young Adults: A Study Using Machine Learning.

Failure to obtain the recommended 7−9 h of sleep has been associated with injuries in youth and adults. However, most research on the influence of prior night's sleep and gait has been conducted on older adults and clinical populations. Therefore, the objective of this study was to identify individuals who experience partial sleep deprivation and/or sleep extension the prior night using single task gait. Participants (n = 123, age 24.3 ± 4.0 years; 65% female) agreed to participate in this study. Self-reported sleep duration of the night prior to testing was collected. Gait data was collected with inertial sensors during a 2 min walk test. Group differences (<7 h and >9 h, poor sleepers; 7−9 h, good sleepers) in gait characteristics were assessed using machine learning and a post-hoc ANCOVA. Results indicated a correlation (r = 0.79) between gait parameters and prior night's sleep. The most accurate machine learning model was a Random Forest Classifier using the top 9 features, which had a mean accuracy of 65.03%. Our findings suggest that good sleepers had more asymmetrical gait patterns and were better at maintaining gait speed than poor sleepers. Further research with larger subject sizes is needed to develop more accurate machine learning models to identify prior night's sleep using single-task gait.

Skipping breakfast and mood: The role of sleep.

BACKGROUND: Breakfast skipping has been related to poor mood, but the role of sleep in this relationship remains unclear. AIM: To evaluate whether breakfast skipping associated with mood independently of sleep, and whether sleep interacted with breakfast skipping. METHODS: During an in-person research visit, a sample of 329 adults completed questionnaires regarding last night's sleep, current morning breakfast intake, and mid-morning mood states. Sex-stratified linear regression models examined associations between breakfast skipping and mood and interactions with sleep. RESULTS: Among males, those who did not consume breakfast had less vigor independent of sleep (ß=-2.72 with 95% CI -4.91, -0.53). Among females, those who did not consume breakfast had higher feelings of anxiety (ß=1.21 with 95% CI -0.04, 2.47). Interaction analyses revealed that males with longer time to fall asleep and longer night-time awake time had higher depression scores in the presence of breakfast skipping, and females with more night-time awake time and shorter duration had higher fatigue and less vigor if they were also breakfast skippers. CONCLUSION: Breakfast skipping and poor sleep may jointly affect mood.

Associations between Mental Workload and Sleep Quality in a Sample of Young Adults Recruited from a US College Town.

OBJECTIVE: To evaluate associations between perceived mental workload (number of hours spent studying and perceived mental intensity) and sleep quality among young adults. PARTICIPANTS: 656 participants [62% male, median age (IQR) = 20 (19, 21) years] recruited from a US college town. METHODS: As part of an online screener, participants answered questions about perceived workload and sleep quality (Pittsburgh Sleep Quality Index (PSQI)). Number of hours/day of mentally engaging work/study, and mental intensity score were the exposures, categorized into quartiles. Linear regression models were used for continuous sleep quality score, and modified Poisson models were used for poor quality sleep (>5 PSQI score) and individual sleep components, adjusting for sex, age, race, physical activity, and caffeine intake. RESULTS: Higher mental work-hours were associated with lower-quality sleep; those in the highest quartile of mental work-hours had a 28% higher likelihood of poor sleep quality (95% CI 2% to 62%). Higher mental intensity scores were also related to lower quality sleep; comparing the highest to the lowest quartiles, there was a 45% higher probability of being a poor sleeper (95% CI 15% to 83%). Associations with PSQI components were partly sex-specific: while both sexes had associations between mental intensity and short sleep, males had positive associations with poor sleep quality and sleep medication use. Conversely, females with higher mental intensity reported higher-quality sleep overall and lower sleep medication use but lower sleep efficiency. CONCLUSIONS: Higher mental workload is associated with lower overall sleep quality in young adults. Associations with individual sleep quality components differed by sex.

A Pilot Exploratory Proteomics Investigation of Mental Fatigue and Mental Energy.

Fatigue is a common and poorly understood problem that impacts approximately 45% of the United States (US) population. Fatigue has also been associated with fatigue-related driving accidents, school absences, decline in school performance and negative health outcomes. Fatigue has been linked to many diseases and is consistently underreported in medical care. Despite these high financial and societal costs, fatigue is a poorly understood problem and there is no consensus on how to measure fatigue. Proteomics is one of the most unbiased approach to measure differences in the protein levels from various biological fluids in two conditions, i.e. before and after mental exercise, aka fatigue. There are, however, challenges associated with such analyses: proteomics experiments are usually expensive and time consuming and also require a large number of participants. Here, we performed a proteomics experiment of three (pre- and post-fatigue) samples and also three matched controls (pre- and post-non-fatigue). We found no particular protein that has significant changes in fatigue sample upon treatment. We did note a potential association between changes in mental energy and Annexin A1. However, the study has value simply because it is an extra study in the field of fatigue, but also allows other to correlate our results with their results.

Trends in Analysis of Cortisol and Its Derivatives.

Determination of concentration of cortisol in various biological fluids can provide extensive information about a person's health. Historically, cortisol and its derivatives were (and still are) determined using immunoaffinity-based methods such as colorimetric ELISA assay, chemiluminescent immunoassay, fluorescence assays, radioimmunoassay, electrochemiluminescence immunoassay, immunochromatographic test, or sensors and immunosensors. Recently, mass spectrometry (MS)-based methods started to be used in determination of cortisol and its derivatives. These MS methods are net superior to immunoaffinity-based assays, but are not easily applicable and are also time-consuming and price prohibitive. Furthermore the standard MS instruments used are triple quadrupole instruments. Here we review the literature on the MS and non-MS based methods for determination of cortisol and its derivatives and also explore the use of a less used quadrupole-time of flight instrument in determination of these compounds.

Agreement of Air Bike and Treadmill Protocols to Assess Maximal Oxygen Uptake: An Exploratory Study.

Maximal oxygen consumption (V̇O2max) is an important measure of aerobic fitness, with applications in evaluating fitness, designing training programs, and assessing overall health. While treadmill assessments are considered the gold standard, airbikes (ABs) are increasingly popular exercise machines. However, limited research exists on AB-based V̇O2max assessments, particularly regarding agreement with treadmill graded exercise tests. To address this gap, a randomized crossover study was conducted, involving 15 healthy adults (9M, 6F, 7 familiar with AB) aged 30.1 ± 8.6 years. Paired t-tests, intraclass correlation coefficients (ICC), Bland-Altman and Principal component (PC) analyses were used to assess agreement between protocols. The results demonstrated good to excellent agreement in V̇O2max, maximum heart rate (HR), and rating of perceived exertion (ICC range: 0.89-0.92). However, significant differences were observed in several measures, including V̇O2max and maximum HR (p < 0.01). Overall a systematic bias 3.31 mL/kg/min (treadmill > AB, 95%CI[1.67,4.94]) was observed, no proportional bias was present; however, regular AB users (systematic bias: 1.27 (95%CI[0.20,2.34]) mL/kg/min) exhibited higher agreement in V̇O2max measures compared to non-regular users (systematic bias: 5.09 (95%CI[3.69,6.49]) mL/kg/min). There were no significant differences in cardiorespiratory coordination, between the AB and the treadmill. These findings suggest that for individuals familiar with the AB, it can be a suitable alternative for assessing V̇O2max compared to the treadmill. Future research with larger samples should focus on developing prediction equations for field AB tests to predict V̇O2max. Practitioners should consider using the AB to assess V̇O2max in individuals who prefer it over running.

No effect of tattoos on local sweat concentrations of select cytokines, cortisol, glucose, blood urea nitrogen, or lactate during exercise.

Due to growing interest in the investigation of exercise induced sweat biomarkers to assess an individual's health and the increasing prevalence of tattoos in the world's population, investigators sought to determine whether local sweat concentrations and excretion rates of epidermal growth factor (EGF), interleukin (IL) -1α, IL-6, IL-8, cortisol, glucose, blood urea nitrogen (BUN), and lactate differ between tattooed and contralateral non-tattooed skin during exercise. Sixteen recreational exercisers [female (50%)] (age = 25-48 years) with ≥ 1 unilateral permanent tattoo [median tattoo age = 6 years, IQR = 5] on the arm/torso completed an outdoor group fitness session. There were no significant differences between tattooed and non-tattooed skin for sweat EGF, IL-1α, IL-8, cortisol, glucose, BUN, or lactate concentrations. There were no significant differences between tattooed and non-tattooed skin for sweat EGF, IL-1α, IL-8, cortisol, glucose, BUN, or lactate excretion rate. Findings suggest that permanent tattoos older than 1 year may not impact local sweat EGF, IL-1α, IL-8, cortisol, glucose, BUN, and lactate concentrations or excretion rates during exercise.Clinical trial identifier NCT04920266 was registered on June 9, 2021.

Correlates of depressive mood among graduate-level allied health students: An exploratory study examining trait energy and fatigue.

Objective: The objective of this study was to identify factors associated with the occurrence and severity of depressive mood states among graduate-level allied health students. Participants: Students (N = 77) completed this study. Methods: Participants completed a series of self-reported surveys measuring moods, lifestyle behaviors, trait mental and physical energy and fatigue, and objective assessments of Trail-Making Test Part-B, and muscle oxygen consumption. Multiple backwards linear regression models were fitted to identify factors associated with depressive mood states. Results: When accounting for all subjects, increased severity of depressive mood states was associated with worse sleep quality (SQ), increased sitting time (ST), and trait physical fatigue (TPF). When examining subjects reporting depressive mood states, increased severity of depressive mood states was associated with worse SQ, increased ST, decreased mental workload on non-school days, and trait physical energy (TPE). Conclusion: Adjustments in lifestyle factors such as sleep, mental workload, and ST, may ameliorate depressive mood states.

An Intense Bout of Acute Aerobic Exercise, but Not a Carbohydrate Supplement, Improves Cognitive Task Performance in a Sample of Black, Indigenous, and People of Color (BIPOC) Student Athletes.

BACKGROUND: There are contradictory findings in the literature on whether an acute bout of aerobic exercise leads to a post-exercise improvement in cognitive function (CF). Moreover, participants used in the published literature are not representative of the racial make-up of sport or tactical populations. METHODS: A randomized crossover design was incorporated, with participants randomly consuming water or a carbohydrate sports drink within the first 3 min of a graded maximal exercise test (GMET) conducted in a laboratory. Twelve self-identified African American participants, (seven males, five females, age = 21.42 ± 2.38 years, height = 174.94 ± 12.55 cm, mass = 82.45 ± 33.09 kg) completed both testing days. Participants completed the CF tests immediately pre- and post-GMET. CF was assessed with the Stroop color and word task (SCWT) and concentration task grid (CTG). Participants completed the GMET when they reported a score of 20 on the Borg ratings of perceived exertion scale. RESULTS: Time to complete the SCWT incongruent task (p < 0.001) and CTG performance (p < 0.001) significantly improved post-GMET in both conditions. VO2max was positively correlated with pre- and post-GMET SCWT performance. CONCLUSIONS: The findings of our study suggest that an acute bout of maximal exercise significantly improves CF. Additionally, cardiorespiratory fitness is positively associated with CF in our sample of student athletes from a historically Black college and university.

Depression, Anxiety, Energy, and Fatigue Among Nurses Who Cared for Patients During the COVID-19 Pandemic: A Cross-Sectional Study.

Purpose of Study: Nurses around the world have faced challenges during the coronavirus disease 2019 (COVID-19) pandemic. This study examined the association between depression and anxiety and trait energy and trait fatigue, and baseline health status and work characteristics. Design of Study: A cross-sectional study. Methods: A survey was conducted to collect self-reported data from nurses involved in patient care in Northern Virginia. Depression and anxiety were assessed using the Patient-Reported Outcomes Measurement Information System (PROMIS) depression and anxiety scales. To measure trait energy and trait fatigue, the Mental and Physical State and Trait Energy and Fatigue Scale (MPSTEFS) was used. Findings: There was a significant association between depression and energy (b=-0.46, t = -1.78, p < .001) and loneliness (b=1.38, t = 4.00, p < .001) and increased alcohol use (b=2.11, t = 2.04, p = .045). We also found that nurses with depression were significantly more likely to seek mental health counseling (b=-2.91, t = 2.54, p = 0.013), which was also the case for anxiety (b=3.13, t = 2.14, p = .036). Conclusions: Our study highlights the mental health burden among nurses who worked in the early phase of the COVID-19 pandemic and its association with increased alcohol use and loneliness. The findings may help healthcare leaders identify early signals of deterioration in nurses' well-being.

Association between Self-reported Sleep Quality and Single-task Gait in Young Adults: A Study Using Machine Learning.

Objective The objective of the present study was to find biomechanical correlates of single-task gait and self-reported sleep quality in a healthy, young population by replicating a recently published study. Materials and Methods Young adults ( n = 123) were recruited and were asked to complete the Pittsburgh Sleep Quality Inventory to assess sleep quality. Gait variables ( n = 53) were recorded using a wearable inertial measurement sensor system on an indoor track. The data were split into training and test sets and then different machine learning models were applied. A post-hoc analysis of covariance (ANCOVA) was used to find statistically significant differences in gait variables between good and poor sleepers. Results AdaBoost models reported the highest correlation coefficient (0.77), with Support-Vector classifiers reporting the highest accuracy (62%). The most important features associated with poor sleep quality related to pelvic tilt and gait initiation. This indicates that overall poor sleepers have decreased pelvic tilt angle changes, specifically when initiating gait coming out of turns (first step pelvic tilt angle) and demonstrate difficulty maintaining gait speed. Discussion The results of the present study indicate that when using traditional gait variables, single-task gait has poor accuracy prediction for subjective sleep quality in young adults. Although the associations in the study are not as strong as those previously reported, they do provide insight into how gait varies in individuals who report poor sleep hygiene. Future studies should use larger samples to determine whether single task-gait may help predict objective measures of sleep quality especially in a repeated measures or longitudinal or intervention framework.

Sleep quality in relation to trait energy and fatigue: an exploratory study of healthy young adults.

Objectives: To evaluate how sleep quality predicts the trait aspect of mental and physical energy versus fatigue within a healthy non-obese adult population. Material and Methods: A study population of 495 adults completed an online survey concerning trait energy and fatigue as well as sleep quality. Bivariate and adjusted analysis examined whether sleep quality, measured from the Pittsburgh sleep quality instrument, associated with physical and mental trait energy and fatigue (4 separate constructs). Adjusted analysis included caffeine consumption, polyphenol consumption, current mood, perceived mental workload, and physical activity. Results: Bivariate analysis showed that both physical and mental fatigue were associated with sleep quality, while physical and mental energy were not. However, after adjustment for potential confounders, sleep quality was associated with mental fatigue and physical energy (not physical fatigue). Conclusion: Findings suggest that improvement in sleep quality among healthy young adults may affect certain aspects of physical versus mental energy and fatigue more strongly than others.

Energy drink usage by students attending an online university.

Objective: This study determined the frequency, reasons for, and side effects of energy drinks (ED) consumption among online students. Participants: Students attending an online university. Methods: Participants were recruited by email and completed a 59-question survey about their prior months ED practices using a combination of validated surveys previously published examining similar constructs in on-campus students. Results: 307 students (age = 32.4 ± 6.5yrs) completed the survey, and 88% reported consuming EDs. Students' reasons for consuming ED included school (p < .001), work (p < .001), an event/competition (p < .001), pick me up (p < .001), lack of rest (p < .001), more energy (p < .001), and staying awake while driving (p < .001). Only individuals who consumed >10 ED/month reported side effects of headaches (p = .01) and speeding (p = .01). Conclusions: In our sample, a majority of the participants reported consuming ED for various daily activities. Only frequent consumers reported side effects suggesting they had become habituated to caffeine since they drank EDs despite experiencing side effects.

Preventive Medicine via Lifestyle Medicine Implementation Practices Should Consider Individuals' Complex Psychosocial Profile.

Noncommunicable chronic diseases are associated with lifestyle behaviors. Psychological and social factors may influence the adoption of such behaviors. Being mentally and physically energized or fatigued may influence the intention-behavior gap of healthy lifestyle adoption accordingly. We investigated the associations of age, sex, lifestyle behaviors, mood, and mental and physical energy and fatigue at both the trait and state levels. The participants (N = 670) completed questionnaires assessing their sleep, mood, mental and physical state energy and fatigue, physical activity, mental workload, and diet. The ordinary least squares regression models revealed an overlap between the mental state and trait energy levels for males who consume polyphenols, have a high mental workload, and sleep well. Being younger, having a high stress level, bad sleep habits, and being confused and depressed were associated with high mental fatigue. Physical energy and fatigue shared the same commonalities with the previous results, with greater discrepancies observed between the state and trait indicators compared to that between mental energy and fatigue. Diet and stress management seem to be predictors of high physical energy, and females report higher physical fatigue levels. Health care professionals should consider this psychosocial complex profiling in their differential diagnosis and when one is implementing lifestyle behavioral changes to address the facets of preventive medicine, wellness, and health promotion.

Relationships between grit and lifestyle factors in undergraduate college students during the COVID-19 pandemic.

Objective: To investigate the influence of grit on physical activity, sleep and diet in undergraduate students during the COVID-19 pandemic. Participants: 125 undergraduate students participated in the study. Participants completed an online survey while enrolled in an online class during June, 2020. Methods: The online questionairre featured the following validated survey instruments: International Physical Activity Questionnaire Short Form, Pittsburgh Sleep Quality Index, the Rapid Eating Assessment for Participants Short Form and the grit short form. Effects of grit on lifestyle behaviors were explored using several statistical approaches. Results: We found that individuals with more grit reported better eating and sleeping behaviors compared to those with less grit. However, we did not find an influence of grit on physical activity or sitting time. Conclusion: Our findings support that personality traits encompassed in grit contribute to college students reporting healthier dietary habits and better sleep quality during a global pandemic.

Influence of grit and healthy lifestyle behaviors on anxiety and depression in US adults at the beginning of the COVID-19 pandemic: Cross-sectional study.

Background: The coronavirus disease 2019 (COVID-19) pandemic altered lifestyles and impacted mental health of many adults. Engaging in physical activity, avoiding prolonged sitting, and consuming a healthy diet improve mental health. The current study investigated the association between health-related lifestyle behaviors on feelings of anxiety and depression in adults during the early stages of the COVID-19 pandemic. Methods: Adults (n=796) living in the United States completed an internet-based survey in Spring 2020 that included validated survey instruments for moods, physical activity, sitting and dietary behaviors. Multivariate multiple regression models were used to assess the association between health-related lifestyle behaviors and feelings of anxiety and depression. Results: A majority (70.7%; 95% CI: [0.607, 0.807]) of participants met physical activity (PA) guidelines, 43.7% (95% CI: [0.287, 0.587]) sat for ≥ 8 hours per day, and 87.7% (95% CI [0.807, 0.947]) ate a healthy diet. Our final models explained 6.2% and 9.8% of the variance in anxiety and depression, respectively. Vigorous PA (anxiety: B=-0.111, 95% CI: [-0.171,0.000]; depression: B=-0.111, 95% CI: [-0.186,-0.037]) and dietary behaviors (anxiety: B=-0.112, 95% CI: [-0.180,-0.444]; depression: B=-0.112, 95% CI: [-0.213,-0.076]) were associated with reduced feelings of anxiety and depression while sitting time (anxiety: B=0.119, 95% CI: [0.000,0.199]; depression: B=0.119, 95% CI: [0.199,0.199]) were associated with greater feelings of anxiety and depression. Conclusion: Engaging in vigorous physically activity, reducing sitting time, and consuming a healthy diet was associated with reduced feelings of anxiety and depression during the early part of the pandemic. The aforementioned modifiable lifestyle behaviors are independent of each other suggesting improvements in one behavior may improve feelings of anxiety and depression.