122 research outputs found

    Stress detection using wearable physiological sensors

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    As the population increases in the world, the ratio of health carers is rapidly decreasing. Therefore, there is an urgent need to create new technologies to monitor the physical and mental health of people during their daily life. In particular, negative mental states like depression and anxiety are big problems in modern societies, usually due to stressful situations during everyday activities including work. This paper presents a machine learning approach for stress detection on people using wearable physiological sensors with the �final aim of improving their quality of life. The presented technique can monitor the state of the subject continuously and classify it into "stressful" or "non-stressful" situations. Our classification results show that this method is a good starting point towards real-time stress detection

    Cardiorespiratory Fitness Estimation Based on Heart Rate and Body Acceleration in Adults With Cardiovascular Risk Factors : Validation Study

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    Publisher Copyright: © Antti-Pekka E Rissanen, Mirva Rottensteiner, Urho M Kujala, Jari L O Kurkela, Jan Wikgren, Jari A Laukkanen. Originally published in JMIR Cardio (https://cardio.jmir.org), 25.10.2022. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Cardio, is properly cited. The complete bibliographic information, a link to the original publication on https://cardio.jmir.org, as well as this copyright and license information must be included.Background: Cardiorespiratory fitness (CRF) is an independent risk factor for cardiovascular morbidity and mortality. Adding CRF to conventional risk factors (eg, smoking, hypertension, impaired glucose metabolism, and dyslipidemia) improves the prediction of an individual's risk for adverse health outcomes such as those related to cardiovascular disease. Consequently, it is recommended to determine CRF as part of individualized risk prediction. However, CRF is not determined routinely in everyday clinical practice. Wearable technologies provide a potential strategy to estimate CRF on a daily basis, and such technologies, which provide CRF estimates based on heart rate and body acceleration, have been developed. However, the validity of such technologies in estimating individual CRF in clinically relevant populations is poorly known. Objective: The objective of this study is to evaluate the validity of a wearable technology, which provides estimated CRF based on heart rate and body acceleration, in working-aged adults with cardiovascular risk factors. Methods: In total, 74 adults (age range 35-64 years; n=56, 76% were women; mean BMI 28.7, SD 4.6 kg/m2) with frequent cardiovascular risk factors (eg, n=64, 86% hypertension; n=18, 24% prediabetes; n=14, 19% type 2 diabetes; and n=51, 69% metabolic syndrome) performed a 30-minute self-paced walk on an indoor track and a cardiopulmonary exercise test on a treadmill. CRF, quantified as peak O2 uptake, was both estimated (self-paced walk: a wearable single-lead electrocardiogram device worn to record continuous beat-to-beat R-R intervals and triaxial body acceleration) and measured (cardiopulmonary exercise test: ventilatory gas analysis). The accuracy of the estimated CRF was evaluated against that of the measured CRF. Results: Measured CRF averaged 30.6 (SD 6.3; range 20.1-49.6) mL/kg/min. In all participants (74/74, 100%), mean difference between estimated and measured CRF was −0.1 mL/kg/min (P = .90), mean absolute error was 3.1 mL/kg/min (95% CI 2.6-3.7), mean absolute percentage error was 10.4% (95% CI 8.5-12.5), and intraclass correlation coefficient was 0.88 (95% CI 0.80-0.92). Similar accuracy was observed in various subgroups (sexes, age, BMI categories, hypertension, prediabetes, and metabolic syndrome). However, mean absolute error was 4.2 mL/kg/min (95% CI 2.6-6.1) and mean absolute percentage error was 16.5% (95% CI 8.6-24.4) in the subgroup of patients with type 2 diabetes (14/74, 19%). Conclusions: The error of the CRF estimate, provided by the wearable technology, was likely below or at least very close to the clinically significant level of 3.5 mL/kg/min in working-aged adults with cardiovascular risk factors, but not in the relatively small subgroup of patients with type 2 diabetes. From a large-scale clinical perspective, the findings suggest that wearable technologies have the potential to estimate individual CRF with acceptable accuracy in clinically relevant populations.Peer reviewe

    The impact of lifestyle factors on the intensity of adverse effects in single and repeated session protocols of transcranial electrical stimulation : an exploratory pilot study

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    Transcranial electrical stimulation (tES) has shown promise in the treatment of conditions such as depression and chronic pain with mild-to-moderate adverse effects (AEs). Few previous studies have attempted to identify factors predicting tES-induced AEs. In particular, AEs resulting from repeated sessions of tES remain understudied. We conducted an exploratory retrospective analysis of two independent randomized controlled studies to investigate whether lifestyle factors (i.e. chronic alcohol use, smoking, exercise, and quality and length of sleep) modify the severity and frequency of tES-induced AEs, and evaluated the progression of AEs over repeated sessions. We utilized two double-blinded samples: 1) a male sample (n=82) randomized to receive transcranial direct current stimulation (tDCS) or sham for 5 days, and 2) a mixed-sex sample (n=60) who received both transcranial random noise stimulation (tRNS) and sham in a crossover setting. The severity of AEs was recorded on a scale of 0-100. The data was analysed using negative binomial models. In addition, we performed power calculations and, to guide future research, evaluated the numbers of individuals needed to detect non-significant observations as significant. By day 5, the tDCS group experienced more sensations under the electrodes than the sham group. Alcohol use, smoking, exercise, or quality or duration of sleep did not appear to be associated with the intensity of the AEs. The subsequent power analyses indicated that substantially larger samples would be needed to detect the observed associations as significant. Repetitive sessions do not appear to introduce additional AE burden to individuals receiving either tDCS or tRNS, at least with protocols lasting up to 5 days. Alcohol use, smoking, exercise, or quality or duration of sleep appear to only have an effect of negligible size, if any, on AEs induced by tDCS or tRNS, and studies with sample sizes ranging from roughly 100 individuals to hundreds of thousands of individuals would be required to detect such effects as significant

    Measuring psychosocial stress with heart rate variability-based methods in different health and age groups

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    Objective. Autonomic nervous system function and thereby bodily stress and recovery reactions may be assessed by wearable devices measuring heart rate (HR) and its variability (HRV). So far, the validity of HRV-based stress assessments has been mainly studied in healthy populations. In this study, we determined how psychosocial stress affects physiological and psychological stress responses in both young (18-30 years) and middle-aged (45-64 years) healthy individuals as well as in patients with arterial hypertension and/or either prior evidence of prediabetes or type 2 diabetes. We also studied how an HRV-based stress index (Relax-Stress Intensity, RSI) relates to perceived stress (PS) and cortisol (CRT) responses during psychosocial stress. Approach. A total of 197 participants were divided into three groups: (1) healthy young (HY, N = 63), (2) healthy middle-aged (HM, N = 61) and (3) patients with cardiometabolic risk factors (Pts, N = 73, 32-65 years). The participants underwent a group version of Trier Social Stress Test (TSST-G). HR, HRV (quantified as root mean square of successive differences of R-R intervals, RMSSD), RSI, PS, and salivary CRT were measured regularly during TSST-G and a subsequent recovery period. Main results. All groups showed significant stress reactions during TSST-G as indicated by significant responses of HR, RMSSD, RSI, PS, and salivary CRT. Between-group differences were also observed in all measures. Correlation and regression analyses implied RSI being the strongest predictor of CRT response, while HR was more closely associated with PS. Significance. The HRV-based stress index mirrors responses of CRT, which is an independent marker for physiological stress, around TSST-G. Thus, the HRV-based stress index may be used to quantify physiological responses to psychosocial stress across various health and age groups.Peer reviewe

    Hippocampal state-dependent behavioral reflex to an identical sensory input in rats.

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    We examined the local field potential of the hippocampus to monitor brain states during a conditional discrimination task, in order to elucidate the relationship between ongoing brain states and a conditioned motor reflex. Five 10-week-old Wistar/ST male rats underwent a serial feature positive conditional discrimination task in eyeblink conditioning using a preceding light stimulus as a conditional cue for reinforced trials. In this task, a 2-s light stimulus signaled that the following 350-ms tone (conditioned stimulus) was reinforced with a co-terminating 100-ms periorbital electrical shock. The interval between the end of conditional cue and the onset of the conditioned stimulus was 4±1 s. The conditioned stimulus was not reinforced when the light was not presented. Animals successfully utilized the light stimulus as a conditional cue to drive differential responses to the identical conditioned stimulus. We found that presentation of the conditional cue elicited hippocampal theta oscillations, which persisted during the interval of conditional cue and the conditioned stimulus. Moreover, expression of the conditioned response to the tone (conditioned stimulus) was correlated with the appearance of theta oscillations immediately before the conditioned stimulus. These data support hippocampal involvement in the network underlying a conditional discrimination task in eyeblink conditioning. They also suggest that the preceding hippocampal activity can determine information processing of the tone stimulus in the cerebellum and its associated circuits

    Longer Leukocyte Telomere Length Is Associated with Smaller Hippocampal Volume among Non-Demented APOE ε3/ε3 Subjects

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    Telomere length shortens with cellular division, and leukocyte telomere length is used as a marker for systemic telomere length. The hippocampus hosts adult neurogenesis and is an important structure for episodic memory, and carriers of the apolipoprotein E ε4 allele exhibit higher hippocampal atrophy rates and differing telomere dynamics compared with non-carriers. The authors investigated whether leukocyte telomere length was associated with hippocampal volume in 57 cognitively intact subjects (29 ε3/ε3 carriers; 28 ε4 carriers) aged 49–79 yr. Leukocyte telomere length correlated inversely with left (rs = −0.465; p = 0.011), right (rs = −0.414; p = 0.025), and total hippocampus volume (rs = −0.519; p = 0.004) among APOE ε3/ε3 carriers, but not among ε4 carriers. However, the ε4 carriers fit with the general correlation pattern exhibited by the ε3/ε3 carriers, as ε4 carriers on average had longer telomeres and smaller hippocampi compared with ε3/ε3 carriers. The relationship observed can be interpreted as long telomeres representing a history of relatively low cellular proliferation, reflected in smaller hippocampal volumes. The results support the potential of leukocyte telomere length being used as a biomarker for tapping functional and structural processes of the aging brain

    The impact of lifestyle factors on the intensity of adverse effects in single and repeated session protocols of transcranial electrical stimulation: an exploratory pilot study

    Get PDF
    Transcranial electrical stimulation (tES) has shown promise in the treatment of conditions such as depression and chronic pain with mild-to-moderate adverse effects (AEs). Few previous studies have attempted to identify factors predicting tES-induced AEs. In particular, AEs resulting from repeated sessions of tES remain understudied. We conducted an exploratory retrospective analysis of two independent randomized controlled studies to investigate whether lifestyle factors (i.e. chronic alcohol use, smoking, exercise, and quality and length of sleep) modify the severity and frequency of tES-induced AEs, and evaluated the progression of AEs over repeated sessions. We utilized two double-blinded samples: 1) a male sample (n=82) randomized to receive transcranial direct current stimulation (tDCS) or sham for 5 days, and 2) a mixed-sex sample (n=60) who received both transcranial random noise stimulation (tRNS) and sham in a crossover setting. The severity of AEs was recorded on a scale of 0-100. The data was analysed using negative binomial models. In addition, we performed power calculations and, to guide future research, evaluated the numbers of individuals needed to detect non-significant observations as significant. By day 5, the tDCS group experienced more sensations under the electrodes than the sham group. Alcohol use, smoking, exercise, or quality or duration of sleep did not appear to be associated with the intensity of the AEs. The subsequent power analyses indicated that substantially larger samples would be needed to detect the observed associations as significant. Repetitive sessions do not appear to introduce additional AE burden to individuals receiving either tDCS or tRNS, at least with protocols lasting up to 5 days. Alcohol use, smoking, exercise, or quality or duration of sleep appear to only have an effect of negligible size, if any, on AEs induced by tDCS or tRNS, and studies with sample sizes ranging from roughly 100 individuals to hundreds of thousands of individuals would be required to detect such effects as significant

    Learning to Learn: Theta Oscillations Predict New Learning, which Enhances Related Learning and Neurogenesis

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    Animals in the natural world continuously encounter learning experiences of varying degrees of novelty. New neurons in the hippocampus are especially responsive to learning associations between novel events and more cells survive if a novel and challenging task is learned. One might wonder whether new neurons would be rescued from death upon each new learning experience or whether there is an internal control system that limits the number of cells that are retained as a function of learning. In this experiment, it was hypothesized that learning a task that was similar in content to one already learned previously would not increase cell survival. We further hypothesized that in situations in which the cells are rescued hippocampal theta oscillations (3–12 Hz) would be involved and perhaps necessary for increasing cell survival. Both hypotheses were disproved. Adult male Sprague-Dawley rats were trained on two similar hippocampus-dependent tasks, trace and very-long delay eyeblink conditioning, while recording hippocampal local-field potentials. Cells that were generated after training on the first task were labeled with bromodeoxyuridine and quantified after training on both tasks had ceased. Spontaneous theta activity predicted performance on the first task and the conditioned stimulus induced a theta-band response early in learning the first task. As expected, performance on the first task correlated with performance on the second task. However, theta activity did not increase during training on the second task, even though more cells were present in animals that had learned. Therefore, as long as learning occurs, relatively small changes in the environment are sufficient to increase the number of surviving neurons in the adult hippocampus and they can do so in the absence of an increase in theta activity. In conclusion, these data argue against an upper limit on the number of neurons that can be rescued from death by learning
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