scholarly journals Within-Subject Associations between Mood Dimensions and Non-exercise Activity: An Ambulatory Assessment Approach Using Repeated Real-Time and Objective Data

2016 ◽  
Vol 7 ◽  
Author(s):  
Markus Reichert ◽  
Heike Tost ◽  
Iris Reinhard ◽  
Alexander Zipf ◽  
Hans-Joachim Salize ◽  
...  
2014 ◽  
Vol 25 (4) ◽  
pp. 279-287 ◽  
Author(s):  
Stefan Hey ◽  
Panagiota Anastasopoulou ◽  
André Bideaux ◽  
Wilhelm Stork

Ambulatory assessment of emotional states as well as psychophysiological, cognitive and behavioral reactions constitutes an approach, which is increasingly being used in psychological research. Due to new developments in the field of information and communication technologies and an improved application of mobile physiological sensors, various new systems have been introduced. Methods of experience sampling allow to assess dynamic changes of subjective evaluations in real time and new sensor technologies permit a measurement of physiological responses. In addition, new technologies facilitate the interactive assessment of subjective, physiological, and behavioral data in real-time. Here, we describe these recent developments from the perspective of engineering science and discuss potential applications in the field of neuropsychology.


2009 ◽  
Vol 14 (2) ◽  
pp. 109-119 ◽  
Author(s):  
Ulrich W. Ebner-Priemer ◽  
Timothy J. Trull

Convergent experimental data, autobiographical studies, and investigations on daily life have all demonstrated that gathering information retrospectively is a highly dubious methodology. Retrospection is subject to multiple systematic distortions (i.e., affective valence effect, mood congruent memory effect, duration neglect; peak end rule) as it is based on (often biased) storage and recollection of memories of the original experience or the behavior that are of interest. The method of choice to circumvent these biases is the use of electronic diaries to collect self-reported symptoms, behaviors, or physiological processes in real time. Different terms have been used for this kind of methodology: ambulatory assessment, ecological momentary assessment, experience sampling method, and real-time data capture. Even though the terms differ, they have in common the use of computer-assisted methodology to assess self-reported symptoms, behaviors, or physiological processes, while the participant undergoes normal daily activities. In this review we discuss the main features and advantages of ambulatory assessment regarding clinical psychology and psychiatry: (a) the use of realtime assessment to circumvent biased recollection, (b) assessment in real life to enhance generalizability, (c) repeated assessment to investigate within person processes, (d) multimodal assessment, including psychological, physiological and behavioral data, (e) the opportunity to assess and investigate context-specific relationships, and (f) the possibility of giving feedback in real time. Using prototypic examples from the literature of clinical psychology and psychiatry, we demonstrate that ambulatory assessment can answer specific research questions better than laboratory or questionnaire studies.


2019 ◽  
Vol 151 ◽  
pp. 551-558 ◽  
Author(s):  
Emad Kasaeyan Naeini ◽  
Iman Azimi ◽  
Amir M. Rahmani ◽  
Pasi Liljeberg ◽  
Nikil Dutt

2018 ◽  
Vol 9 ◽  
Author(s):  
Elena D. Koch ◽  
Heike Tost ◽  
Urs Braun ◽  
Gabriela Gan ◽  
Marco Giurgiu ◽  
...  

Coatings ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 55 ◽  
Author(s):  
Fodan Deng ◽  
Ying Huang ◽  
Fardad Azarmi

Coatings, either soft or hard, are commonly used to protect steel against corrosion for longer service life. With coatings, assessing the corrosion behavior and status of the substrate is challenging without destructive analysis. In this paper, fiber Bragg (FBG) grating sensors were proposed to nondestructively evaluate the corrosion behavior of steel coated with two popular coatings, including the polymeric and wire arc sprayed Al-Zn coating. Laboratory accelerated corrosion tests demonstrated that the embedded FBG sensors inside both the soft and hard coatings can effectively quantify the corrosion rate, monitor the corrosion progress, and detect the coating damages and crack propagation of coated steel in real time. The laboratory electrochemical corrosion test on the wire arc sprayed Al-Zn coating validated the proposed embedded FBG sensor method with a good agreement in comparison. The proposed sensing platform provides an alternative nondestructive real-time corrosion assessment approach for coated steel in the field.


10.29007/h37n ◽  
2019 ◽  
Author(s):  
Terri Heglar ◽  
Andrew Penrose ◽  
Austin Yount ◽  
Kristine Galek ◽  
Yantao Shen ◽  
...  

The CTAR All-Star is a system consisting of a rubber ball, a pressure sensor, and a bluetooth transmitter paired with a cross-platform mobile application. The device is used as a rehabilitation tool for people with dysphagia in a similar fashion to the traditional chin tuck against resistance (CTAR) exercise by squeezing a ball between the chin and upper chest. The mobile device monitors and displays the pressure inside the ball on a real-time graph allowing the patient to follow exercise routines set by Speech-Language Pathologists. Additionally, the application stores exercise data that can be used to both monitor the patient's progress over time and provide objective data for future research purposes.


Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4400
Author(s):  
Syed Faraz Naqvi ◽  
Syed Saad Azhar Ali ◽  
Norashikin Yahya ◽  
Mohd Azhar Yasin ◽  
Yasir Hafeez ◽  
...  

Mental stress has been identified as a significant cause of several bodily disorders, such as depression, hypertension, neural and cardiovascular abnormalities. Conventional stress assessment methods are highly subjective and tedious and tend to lack accuracy. Machine-learning (ML)-based computer-aided diagnosis systems can be used to assess the mental state with reasonable accuracy, but they require offline processing and feature extraction, rendering them unsuitable for real-time applications. This paper presents a real-time mental stress assessment approach based on convolutional neural networks (CNNs). The CNN-based approach afforded real-time mental stress assessment with an accuracy as high as 96%, the sensitivity of 95%, and specificity of 97%. The proposed approach is compared with state-of-the-art ML techniques in terms of accuracy, time utilisation, and quality of features.


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