Sensor technologies have improved the everyday life of human beings through their applications in almost all fields. Sensors are devices that detect changes in the source/environment and collect ...signals, and accordingly, the reaction is designed. There is a range of sources, including light, temperature, movements, and pressure etc., which may be used. A wide range of applications is utilised using innovative sensor technologies in lifestyle, healthcare, fitness, manufacturing, and daily life. In the medical field, the difficulty to take medicine is eased by drug donors fitted with sensors. It reminds them to take medicine via a signal and also supply the necessary medicine at the specified moment. In health care, older individuals, athletes, and risk patients benefit from modern sensor technology. The current industrial trends driving innovation include ultrasound, radar, and non-contact optoelectronic solutions and laser technology. The paper gives a brief overview of the numerous types of sensors that are utilised in everyday life. Various capabilities of sensors for day-to-day healthcare are discussed. Various features, associated nomenclature, and measures for sensors in day-to-day routine life are discussed diagrammatically and finally, the paper identifies and discusses twenty-two significant applications of sensors for daily life. Sensors also produce vital information and exchange data with other connected devices and administration systems when linked to a network. Thus, for the effective running of many companies, sensors are critical. Various types of sensors are used in our daily life, which is more accurate and makes quicker analysis.
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•The types of devices and commonly extracted features for each physiological signal.•The research is divided into laboratory, office, school, automobile and daily life.•Relaxation ...apps and methods that could be applied to reduce extreme stress.•Research directions and open research problems in the topic were identified.
Stress has become a significant cause for many diseases in the modern society. Recently, smartphones, smartwatches and smart wrist-bands have become an integral part of our lives and have reached a widespread usage. This raised the question of whether we can detect and prevent stress with smartphones and wearable sensors. In this survey, we will examine the recent works on stress detection in daily life which are using smartphones and wearable devices. Although there are a number of works related to stress detection in controlled laboratory conditions, the number of studies examining stress detection in daily life is limited. We will divide and investigate the works according to used physiological modality and their targeted environment such as office, campus, car and unrestricted daily life conditions. We will also discuss promising techniques, alleviation methods and research challenges.
People differ in the way they live their daily lives. For some people, daily life is characterized by multiple and diverse experiences, while others have more stability and routine in their lives. ...However, little is known about how variety in daily life relates to the expression of personality states. The present study examined within-person associations between variety in social partners, places, and activities with state expression. Data came from an ambulatory assessment study (N = 962, Mage = 25.49) with four assessments per day over a period of six consecutive days. The results of the multilevel modeling analyses suggest that variety in daily life is associated with some, but not all, state expressions. For instance, on days when participants experienced a greater variety in activities, they reported being less neurotic and conscientious, but also more agreeable. In addition, the links between all social partners, places, and activities with the expression of the state were examined simultaneously to obtain more detailed information on the multifaceted nature of situation-state expression links. We conclude that variety in daily life has both theoretical and empirical relevance for the expression of personality states.
Objective:
The study aims to compare swimmers’ daily sport life changes caused by the COVID-19 pandemic in the pre-restriction restriction periods.
Material and methods:
Two hundred fifty-one ...competitive swimmers participated in this study (117 females), aged 12-33 years, who had at least 3-year sport experience. Data were collected via a Google Forms survey. Statistically, before using a parametric test, the assumption of normality was verified using the Shapiro-Wilk test. A paired t-test was performed for one variable. Variables were presented as frequencies and percentages, according to feedbacks received. The Chi-square test was used to compare variables.
Resultsː
There were no significant differences related to the changes caused by COVID-19 between genders (p>0.05). Statistically significant increase in training frequency, decrease in swimming training sessions, increase in dry-land training sessions, and changes of daily training time periods occurred during restriction compared with the pre-restriction period.
Conclusionsː
Findings of this study reveal that the swimmers' athletic lives were negatively affected during the restriction period due to COVID-19.
The direct growth of uniform graphene disks and their continuous film is achieved by exploiting the molten state of glass. The use of molten glass enables highly uniform nucleation and an enhanced ...growth rate (tenfold) of graphene, as compared to those scenarios on commonly used insulating solids. The obtained graphene glasses show promising application potentials in daily‐life scenarios such as smart heating devices and biocompatible cell‐culture mediums.
How pervasive is mind wandering, really? Seli, Paul; Beaty, Roger E.; Cheyne, James Allan ...
Consciousness and cognition,
November 2018, 2018-11-00, 20181101, Volume:
66
Journal Article
Peer reviewed
Open access
•Assessed daily-life mind wandering (MW) with dichotomous and continuous probes.•Estimates of daily-life MW varied dramatically depending on the probe used.•Results indicate that seeking a single ...value for MW is not very psychologically informative.
Recent claims that people spend 30–50% of their waking lives mind wandering (Killingsworth & Gilbert, 2010; Kane et al., 2007) have become widely accepted and frequently cited. While acknowledging attention to be inconstant and wavering, and mind wandering to be ubiquitous, we argue and present evidence that such simple quantitative estimates are misleading and potentially meaningless without serious qualification. Mind-wandering estimates requiring dichotomous judgments of inner experience rely on questionable assumptions about how such judgments are made, and the resulting data do not permit straightforward interpretation. We present evidence that estimates of daily-life mind wandering vary dramatically depending on the response options provided. Offering participants a range of options in estimating task engagement yielded variable mind-wandering estimates, from approximately 60% to 10%, depending on assumptions made about how observers make introspective judgments about their mind-wandering experiences and how they understand what it means to be on- or off-task.
Objective
To test whether polygenic risk score for schizophrenia (PRS‐S) interacts with childhood adversity and daily‐life stressors to influence momentary mental state domains (negative affect, ...positive affect, and subtle psychosis expression) and stress‐sensitivity measures.
Methods
The data were retrieved from a general population twin cohort including 593 adolescents and young adults. Childhood adversity was assessed using the Childhood Trauma Questionnaire. Daily‐life stressors and momentary mental state domains were measured using ecological momentary assessment. PRS‐S was trained on the latest Psychiatric Genetics Consortium schizophrenia meta‐analysis. The analyses were conducted using multilevel mixed‐effects tobit regression models.
Results
Both childhood adversity and daily‐life stressors were associated with increased negative affect, decreased positive affect, and increased subtle psychosis expression, while PRS‐S was only associated with increased positive affect. No gene–environment correlation was detected. There is novel evidence for interaction effects between PRS‐S and childhood adversity to influence momentary mental states negative affect (b = 0.07, P = 0.013), positive affect (b = −0.05, P = 0.043), and subtle psychosis expression (b = 0.11, P = 0.007) and stress‐sensitivity measures.
Conclusion
Exposure to childhood adversities, particularly in individuals with high PRS‐S, is pleiotropically associated with emotion dysregulation and psychosis proneness.
The advantages of using naturalistic virtual reality (VR) environments based on everyday life tasks for cognitive intervention in the elderly are not yet well understood. The literature suggests that ...the similarity of such exercises with real life activities may improve generalizability by extending the transfer of gains of training to everyday living. This study aimed to investigate the gains associated with this ecologically-oriented virtual reality cognitive stimulation (VR-CS) versus standard cognitive stimulation in the elderly. Forty-three healthy older adults were divided into two groups: an experimental group underwent a VR-based cognitive stimulation and an active control group underwent a paper-and-pencil cognitive stimulation. The outcomes assessed at the pre-treatment and posttreatment assessment consisted in well-established tests for cognitive and executive functioning, depression, subjective well-being, and functionality. The results showed positive outcomes on dimensions of general cognition, executive functioning, attention, and visual memory in the group that underwent VR-CS. Improvements in executive functioning in this group was supported by consistent evidence of increases in attention abilities but little evidence of increases in memory abilities. Both effects may have contributed to improvements in general cognition. Further studies are needed to test whether these effects may extend to well-being and functionality in cognitively impaired older adults.
Negative and repetitive self-oriented thinking (rumination) is associated with lower well-being and health. The social context of rumination remains underexplored and mostly centers on marital ...relationships. To embrace the diversity of older adult relationships, this study includes a range of different relationships (e.g., spouses, siblings, friends, etc.) and examines the role of rumination by close others on individual well-being during the coronavirus disease 2019 pandemic.
Using daily diary data from 140 Canadian older adults (M = 72.21 years, standard deviation SD = 5.39, range: 63-87 years, 47% women, 71% university educated) and a close other of their choice (M = 59.95 years, SD = 16.54, range: 18-83 years, 78% women, 81% university educated), this project builds on past research examining daily life rumination dynamics from a dyadic perspective. For 10 days, both dyad members reported their daily rumination and affect quality in the evening.
Multilevel models replicate past work showing that individual rumination was associated with higher negative affect (within-person: b = 0.27, p < .001, between-person: b = 0.57, p < .001) and lower positive affect (within-person: b = -0.18, p < .001, between-person: b = -0.29, p < .001). Importantly, we additionally observed that partner rumination was associated with higher negative affect (b = 0.03, p = .038) and lower positive affect (b = -0.04, p = .023), highlighting the social context of rumination.
Findings illustrate the significance of rumination for the self and others and underline the merit of taking a dyadic perspective on what is typically viewed as an individual-level phenomenon.
The ability to identify and accurately predict abnormal behavior is important for health monitoring systems in smart environments. Specifically, for elderly persons wishing to maintain their ...independence and comfort in their living spaces, abnormal behaviors observed during activities of daily living are a good indicator that the person is more likely to have health and behavioral problems that need intervention and assistance. In this paper, we investigate a variety of deep learning models such as Long Short Term Memory (LSTM), Convolutional Neural Network (CNN), CNN-LSTM and Autoencoder-CNN-LSTM for identifying and accurately predicting the abnormal behaviors of elderly people. The temporal information and spatial sequences collected over time are used to generate models, which can be fitted to the training data and the fitted model can be used to make a prediction. We present an experimental evaluation of these models performance in identifying and predicting elderly persons abnormal behaviors in smart homes, via extensive testing on two public data sets, taking into account different models architectures and tuning the hyperparameters for each model. The performance evaluation is focused on accuracy measure.
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