scholarly journals Connecting Smart Homes to Healthcare Services for People with Neurodegenerative disorders.

2021 ◽  
Vol 9 (4) ◽  
pp. 30-38
Author(s):  
Mhamed Nour
Keyword(s):  
Human Activity ◽  
Central Office ◽  
Health Indicators ◽  
Healthcare Services ◽  
Design Concepts ◽  
Emergency Situations ◽  
People With Dementia ◽  
Past Data ◽  
Human Activity Detection

The objective of this research is to provide an approach for the design of what we have called ‘connected homes’ with a study case for elderly people with dementia living alone. These homes would be connected to a center of surveillance for direct and automatic view of multiple status of the day such as patient security and general health indicators (body temperature, heart rate, blood pressure etc.), detect the intake of meals, eating motivation, humor detection prevention of falls, Alcohol consumption detection, safe use of medicines and emergency situations and other Human Activity Recognition (HAR). The model may also predict situations by using past data accumulation. The model could even send alerts in case of emergency. This service would mean that there would minimum intervention from caregivers thanks to the Artificial Intelligence. As a case study, we proposed a new approach for the conception of connected homes for people with dementia to a central office for automatic human activity detection and help and support accordingly. Such conception includes home design concepts according to standard recommendations and the implementation of new added assistive technology tools to permit the automatic surveillance without violating the ethic requirements. Two installation models will be proposed to consider the financial situation of the patient: a unit or appliance at the patient’s home or a home that is connected to a central office.

Depth-based Human Activity Recognition: vINCI Case Study

2020 ◽  
Author(s):  
Lidia Bajenaru ◽  
Ciprian Dobre ◽  
Radu-Ioan Ciobanu ◽  
Georgiana Dedu ◽  
Silviu-George Pantelimon ◽  
...  
Keyword(s):  
Activity Recognition ◽  
Human Activity ◽  
Human Activity Recognition

Evaluations for New Healthcare Environment Commissioning and Operational Decision Making Using Simulation and Human Factors: A Case Study of an Interventional Trauma Operating Room

2021 ◽  
pp. 193758672199966
Author(s):  
Mirette Dubé ◽  
Jason Laberge ◽  
Elaine Sigalet ◽  
Jonas Shultz ◽  
Christine Vis ◽  
...  
Keyword(s):  
Decision Making ◽  
Human Factors ◽  
Operating Room ◽  
Healthcare Services ◽  
Healthcare Team ◽  
Healthcare Environment ◽  
New Process ◽  
Timely Access ◽  
Operational Decision Making

Purpose: The aim of this article is to provide a case study example of the preopening phase of an interventional trauma operating room (ITOR) using systems-focused simulation and human factor evaluations for healthcare environment commissioning. Background: Systems-focused simulation, underpinned by human factors science, is increasingly being used as a quality improvement tool to test and evaluate healthcare spaces with the stakeholders that use them. Purposeful real-to-life simulated events are rehearsed to allow healthcare teams opportunity to identify what is working well and what needs improvement within the work system such as tasks, environments, and processes that support the delivery of healthcare services. This project highlights salient evaluation objectives and methods used within the clinical commissioning phase of one of the first ITORs in Canada. Methods: A multistaged evaluation project to support clinical commissioning was facilitated engaging 24 stakeholder groups. Key evaluation objectives highlighted include the evaluation of two transport routes, switching of operating room (OR) tabletops, the use of the C-arm, and timely access to lead in the OR. Multiple evaluation methods were used including observation, debriefing, time-based metrics, distance wheel metrics, equipment adjustment counts, and other transport route considerations. Results: The evaluation resulted in several types of data that allowed for informed decision making for the most effective, efficient, and safest transport route for an exsanguinating trauma patient and healthcare team; improved efficiencies in use of the C-arm, significantly reduced the time to access lead; and uncovered a new process for switching OR tabletop due to safety threats identified.

scholarly journals Contactless Interactive Fall Detection and Sleep Quality Estimation for Supporting Elderly with Incipient Dementia

2020 ◽  
Vol 6 (3) ◽  
pp. 388-391
Author(s):  
Roman Siedel ◽  
Tobias Scheck ◽  
Ana C. Perez Grassi ◽  
Julian B. Seuffert ◽  
André Apitzsch ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Assisted Living ◽  
Ambient Assisted Living ◽  
Fall Detection ◽  
Quality Estimation ◽  
Emergency Situations ◽  
People With Dementia ◽  
Affected Person ◽  
Development State ◽  
Current Behaviour

AbstractIn recent years, the demographic change in conjunction with a lack of professional caregivers led to retirement homes reaching capacity. The Alzheimer Disease International stated that over 50 million people suffered from dementia in 2019 worldwide and twice the amount will presumably be effected in 2030. The field of Ambient Assisted Living (AAL) tackles this problem by facilitating technical system-aided everyday life. AUXILIA is such an AAL system and does not only support elderly people with dementia in an early phase, but also monitors their activities to provide behaviour analysis results for care attendants, relatives and physicians. Moreover, the system is capable of recognizing emergency situations like human falls. Furthermore, sleep quality estimation is employed to be able to draw conclusions about the current behaviour of an affected person. This article presents the current development state of AUXILIA.

scholarly journals Machine Learning and LPWAN Based Internet of Things Applications in Healthcare Sector during COVID-19 Pandemic

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1615
Author(s):  
Zeeshan Ali Khan ◽  
Ubaid Abbasi ◽  
Sung Won Kim
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Healthcare Services ◽  
Healthcare Sector ◽  
K Nearest Neighbors ◽  
Iot Applications ◽  
Processing Resources ◽  
Multiple Services ◽  
Applications Of Machine Learning

Low power wide area networks (LPWAN) are comprised of small devices having restricted processing resources and limited energy budget. These devices are connected with each other using communication protocols. Considering their available resources, these devices can be used in a number of different Internet of Things (IoT) applications. Another interesting paradigm is machine learning, which can also be integrated with LPWAN technology to embed intelligence into these IoT applications. These machine learning-based applications combine intelligence with LPWAN and prove to be a useful tool. One such IoT application is in the medical field, where they can be used to provide multiple services. In the scenario of the COVID-19 pandemic, the importance of LPWAN-based medical services has gained particular attention. This article describes various COVID-19-related healthcare services, using the the applications of machine learning and LPWAN in improving the medical domain during the current COVID-19 pandemic. We validate our idea with the help of a case study that describes a way to reduce the spread of any pandemic using LPWAN technology and machine learning. The case study compares k-Nearest Neighbors (KNN) and trust-based algorithms for mitigating the flow of virus spread. The simulation results show the effectiveness of KNN for curtailing the COVID-19 spread.

Hydrological changes in the Rzecin peatland (Puszcza Notecka, Poland) induced by anthropogenic factors: Implications for mire development and carbon sequestration

The Holocene ◽  
2016 ◽  
Vol 27 (5) ◽  
pp. 651-664 ◽  
Author(s):  
Krystyna Milecka ◽  
Grzegorz Kowalewski ◽  
Barbara Fiałkiewicz-Kozieł ◽  
Mariusz Gałka ◽  
Mariusz Lamentowicz ◽  
...  
Keyword(s):  
Carbon Sequestration ◽  
Plant Communities ◽  
Human Activity ◽  
Accumulation Rate ◽  
Carbon Accumulation ◽  
Anthropogenic Factors ◽  
Poor Fen ◽  
History Of ◽  
Carbon Accumulation Rates

Wetlands are very vulnerable ecosystems and sensitive to changes in the ground water table. For the last few thousand years, hydrological balance has also been influenced by human activity. To improve their cropping features, drainage activity and fertilizing were applied. The drainage process led to an abrupt change of environment, the replacement of plant communities and the entire ecosystem. The problem of carbon sequestration is very important nowadays. A higher accumulation rate is related to higher carbon accumulation, but the intensity of carbon sequestration depends on the type of mire, habitat, and climatic zone. The main aim of this article was an examination of the changes in poor-fen ecosystem during the last 200 years in relation to natural and anthropogenic factors, using paleoecological methods (pollen and macrofossils). The second aim was a detailed investigation of the sedimentary record to aid our understanding of carbon sequestration in the poor fen of temperate zone. This case study shows that fens in temperate zones, in comparison with boreal ones, show higher carbon accumulation rates which have been especially intensive over the last few decades. To reconstruct vegetation changes, detailed palynological and macrofossil analyses were done. A 200-year history of the mire revealed that it was influenced by human activity to much degree. However, despite the nearby settlement and building of the drainage ditch, the precious species and plant communities still occur.

The effect of a lollipop on vocally disruptive behavior in a patient with frontotemporal dementia: a case-study

2014 ◽  
Vol 26 (12) ◽  
pp. 2023-2026 ◽  
Author(s):  
W. F. Fick ◽  
J. P. van der Borgh ◽  
S. Jansen ◽  
R. T. C. M. Koopmans
Keyword(s):  
Beneficial Effect ◽  
Knowledge Base ◽  
Frontotemporal Dementia ◽  
Disruptive Behavior ◽  
Treatment Strategies ◽  
Limited Knowledge ◽  
People With Dementia

ABSTRACTA problematic and disturbing behavior which can develop in people with dementia, is vocally disruptive behavior (VDB). To date, the study of VDB is underdeveloped and with only a limited knowledge base. Medications commonly used in VDB have limited benefits and specific risks in patients with dementia. This report details the case of a patient with frontotemporal dementia with VDB, which responded very well by providing a lollipop. Subsequently, we pose theory-based hypotheses in order to try to explain the beneficial effect of this intervention. This may contribute to a better understanding of VDB and possible treatment strategies.

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