• International conference on construction engineering and project management
• /
• 2024.07a
• /
• pp.285-292
• /
• 2024

Physiological devices and immersive technologies are crucial innovations being implemented for construction safety. Physiological devices provide insights into the wellbeing of workers while immersive technologies have a potential to simulate or enhance construction environments. These two technologies present numerous benefits for construction safety and have been extensively implemented in various dimensions. In addition to the individual benefits of these two technologies, combining them presents more opportunities for construction safety research and numerous studies have been conducted using this approach. However, despite promising results achieved by studies which have used this technological combination, no review has been conducted to summarize the findings of these studies. This review therefore summarizes studies that have combined immersive technologies with physiological monitoring for construction safety. A systematic approach is employed, and 24 articles are reviewed. This review highlights four safety aspects which have been explored using a combination of immersive technologies and physiological monitoring. These aspects are (1) Safety training and evaluation (2) Hazard identification (3) Attention assessment and (4) Cognitive strain assessment. In addition, there are three main directions for future research. (1) Future studies should explore other types of immersive technologies such as immersive audio (2) Physiological reactions to hazard exposure should be studied and (3) More multi-physiological approaches should be adopted.

• International conference on construction engineering and project management
• /
• 2024.07a
• /
• pp.471-478
• /
• 2024

Effective physical fatigue monitoring is crucial for ensuring the health, safety, and productivity of construction workers, given the physically demanding nature of their work and the challenging environment in which they operate. In recent years, wearable sensors have shown growing potential for physical fatigue monitoring among construction workers. However, such fatigue assessment methods exhibit a significant gap as they often overlook the impact of inter-individual variability, such as differences in height, weight, and body mass index, on physiological signals that indicate physical fatigue. Therefore, this study aimed to investigate the role of personal factors in altering physiological responses, thereby improving the reliability and accuracy of fatigue monitoring using wearable physiological sensors. To explore the impact of these inter-individual factors, we experimentally analyzed the relationship between personal characteristics, physiological signals, and physical fatigue. Our findings reveal that although the inter-individual factors may not be directly correlated with fatigue levels, they significantly affect fatigue through their influence on physiological signals. Incorporation of these factors into a random forest predictive model significantly enhanced its predictive performance. Furthermore, integrating personal features with other variables to create new features in the physical fatigue prediction model notably improves its accuracy, highlighting the potential for developing personalized fatigue detection systems.

• Journal of Biosystems Engineering
• /
• v.39 no.3
• /
• pp.194-204
• /
• 2014

Purpose: The aim of this study was to develop long-term storage technology for Chinese cabbage in order to extend the period of availability of freshly harvested products. The scope of the paper deals with the use of a cooler with a remote monitoring and control interface in conjunction with use of packaging film. Methods: A cooler with a real time monitoring system was designed as a low-temperature storage facility to control temperature and relative humidity (RH). The effects of storage in high-density polyethylene (HDPE) plastic boxes, 3% chitosan dipping solution, polypropylene film (PEF) with perforations, and mesh packaging bags on physiological responses were investigated. The optimal storage temperature and humidity for 120 days were below $0.5^{\circ}C$ and 90%, respectively. Physiological and biochemical features of cabbage quality were also analyzed: weight loss, texture, and sugar salinity, chlorophyll, reducing sugar, and vitamin C contents. Results: The cooler with a remote monitoring and control interface could be operated by an HMI program. A $0.5^{\circ}C$ temperature and 90% humidity could be remotely controlled within the cooler for 120 days. Postharvest freshness of Chinese cabbages could be maintained up to 120 days depending on the packaging method and operation of the remote monitoring system. In particular, wrapping the cabbages in PEF with perforations resulted in a less than a 5% deterioration in quality. This study provides evidence for efficient performance of plastic films in minimizing post-harvest deterioration and maintaining overall quality of cabbages stored under precise low-temperature conditions with remote monitoring and a control interface. Conclusions: Packaging with a modified plastic film and storage in a precisely controlled cooler with a remote monitoring and control interface could slow down the physiological factors that cause adverse quality changes and thereby increase the shelf life of Chinese cabbage.

• 한국HCI학회:학술대회논문집
• /
• 2006.02a
• /
• pp.960-965
• /
• 2006

Privacy and security are latent problems in pervasive healthcare system. For the sake of protecting health monitoring information, it is necessary to classify and categorize the various contexts in terms of obfuscation. In this paper, we propose the physiological context categorization and specification methodology by exploiting data fusion network for automatic context alignment. In addition, we introduce the methodologies for making various level of physiological context on the context aware application model, which is wear-UCAM. This physiological context has several layers of context according to the level of abstraction such as user-friendly level or parametric level. This mechanism facilitates a user to restrict access to his/her monitoring results based on the level of details in context.

• Journal of the Institute of Convergence Signal Processing
• /
• v.20 no.1
• /
• pp.9-15
• /
• 2019

As the human population increases in the world, the ratio of health doctors is rapidly decreasing. Therefore, it 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 this happens due to stressful situations during everyday activities including work. This paper presents a machine learning approach to reliably estimating the level of human mental stress using wearable physiological sensors. And also, this paper presents an Android- and Arduino-based stress monitoring and relief system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2007.10a
• /
• pp.67-71
• /
• 2007

Recently, a health care need according to the increase of an advanced age population is increasing. The requirement about a health care monitoring is increasing rapidly from general people as well as patient. The requisition about a medical treatment technique and a medical treatment information service is the trend to be expanding. That can be possible minimizing the inconvenience of the patient to take a medical service and continuously monitoring the status of the patient to take a health care service. This paper discusses an implementation of wireless physiological signal monitoring system for health care. The system are composed of the sensor node and monitoring program. The sensor node has the physiological signal measurement part and the wireless communication part. The remote monitoring system has a monitoring program that are communicating the sensor node using bluetooth. The sensor node measured the ECG, pulse wave, blood pressure, Sp02, and heart rate.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.12 no.8
• /
• pp.1401-1407
• /
• 2008

Recently, a health care need according to the increase of an advanced age population is increasing. The requirement about a health care monitoring is increasing rapidly from general people as well as patient. The requisition about a medical treatment technique and a medical treatment information service is the trend to be expanding. That can be possible minimizing the inconvenience of the patient to take a medical service and continuously monitoring the status of the patient to take a health care service. This paper discusses an implementation of wireless physiological signal monitoring system for health care. The system are composed of the sensor node and monitoring program. The sensor node has the physiological signal measurement part and the wireless communication part. The remote monitoring system has a monitoring program that are communicating the sensor node using bluetooth. The sensor node measured the ECG, pulse wave, blood pressure, SpO2, and heart rate.

• The Korean Journal of Rehabilitation Nursing
• /
• v.4 no.1
• /
• pp.94-104
• /
• 2001

The purpose of this study was to analysis of nursing interventions performed by the ICU nurses to the patients with cerebrovascular disorder practically from one university hospital in Seoul. The data were collected from 15 nurses with 86 cerebrovascular disorder cases from one ICU with the questionaire to write frequency of nursing care done by the surveyee from May, 2, 2000 to July, 3, 2000 and the list of 66 nursing interventions selected out of 433 NIC(Nursing Interventions Classification) of Iowa University which were translated into Korean (44 items) and core nursing interventions by ICU nurses (22 items; KIm, Su-Jin, 1997). The data were analysed with SPSS program. The results are as follow : 1. The most frequently used nursing interventions were vital sign monitoring, fall prevention, cerebral edema management, dysreflexia management, neurologic monitoring, cardiac care, communication enhancement, technology management, bed rest care, respiratory monitoring in rank. 2. The most frequently used nursing intervention domains were 'Physiological : Complex', 'Physiological : basic', 'Behavior', 'Safty', 'Health system' in rank. In the domain of physiological : basic, the most frequently used nursing interventions were bed rest care, urinary elimination management, tube care : urinary, physical restraints in rank. In the domain of physiological : complex, the most frequently used nursing interventions were cerebral edema management, dysreflexia management, neurologic monitoring, cardiac care in rank. In the domain of behavior, the most frequently used nursing interventions were communication enhancement, touch, active listening in rank. In the domain of safty, the most frequently used nursing interventions were vital sign monitoring, fall prevention in rank. In the domain of health system, the most frequently used nursing interventions were technology management, specimen management in rank. 3. some difference of the frequency practicing the nursing interventions according to the shift of duties was found. For example, medication administration was common at day duty, touch was practiced at evening duty, temperature regulation was performed.

• 한국HCI학회:학술대회논문집
• /
• 2009.02a
• /
• pp.173-177
• /
• 2009

With the advent of light-weight daily physiological signal monitoring sensors, intelligent inference and analysis method for physiological signal monitoring application, commercialized products and services are released. However, practical constraints still remain for daily physiological signal monitoring. Most devices provide rough health check function and analyze with randomly sampled measurements. In this work, we propose the probabilistic modeling of physiological signal analysis. This model represent the relationship between previous user measurement (history), other group`s type, model and current observation. From the experiment, we found that the personalized analysis with long term regular data shows reliable result and reduces the analyzing errors. In addition, participants agree that the personalized analysis shows reliable and adaptive information than other standard analysis method.

• Journal of Marine Life Science
• /
• v.3 no.2
• /
• pp.87-95
• /
• 2018

To investigate effects of starvation on physiological changes, stress response, and survival of cobitid loach (Misgurnus anguillicaudatus) exposed to sodium nitrite (NaNO₂), a 4-week experiment was conducted. Fewer fish survived in the starved group than those in the fed group during the experiment. Starvation resulted in growth retardation, leading to differences in body length and body depth between fed and starved groups. The fed gorup continued to grow and remained in good condition. Blood chemical analysis (plasma cortisol and glucose) showed significant differences in stress response to nitrite exposure between fed and starved groups (p < 0.05). These results suggest that all parameters employed in this study to assess effects of starvation with NaNO₂ stress are useful information for researching nutritional status in cobitid loach.