GerAmi: Improving Healthcare Delivery in Geriatric Residences

Many countries face an ever-growing need to supply constant care and support for their disabled and elderly populations. In this paper, we've developed geriatric ambient intelligence, an intelligent environment that integrates multiagent systems, mobile devices, RFID, and Wi-Fi technologies to facilitate management and control of geriatric residences. At GerAmi's core is the geriatric agent (GerAg), a deliberative agent that incorporates a case-based planning (CBP) mechanism to optimize work schedules and provide up-to-date patient and facility data. We've successfully implemented a system prototype at a care facility for Alzheimer patients

Autonomous FYDPS Neural Network-Based Planner Agent for Health Care in Geriatric Residences

This paper presents an autonomous intelligent agent developed for health care in geriatric residences. The paper focuses on the construction of an autonomous agent which incorporates a model of human thinking, such as reasoning based on past experiences. The work here presented focuses in the development of the CBP internal structure. The planning mechanism has been implemented by means of a novel FYDPS neural network. The system has been tested and this paper presents the results obtained

TaskCBP: an intelligent agent for task planning in elderly care

This paper presents an autonomous intelligent agent developed for healthcare in geriatric residences. The paper focuses on the role of ambient intelligence in the automation of healthcare services. The work here presented shows the development of an autonomous agent, TaskCBP, which incorporates a model of human thinking, such as reasoning based on past experiences. The planning mechanism integrated within the agent has been implemented by means of a novel QSOR neural network. The system has been tested and this paper presents the results obtaine

Hybrid Multi-Agent System for Alzheimer Health Care

This paper presents a dynamic multi-agent system for monitoring Alzheimer patients’ health care in execution time in geriatric residences. The system architecture implements autonomous deliberative case-based agents with reasoning and planning capabilities, with the ability to operate in wireless devices and capable of obtaining information about the environment through RFID technology. ALZ- MAS description and preliminary results of the prototype in a real environment are presented

Applying a service-oriented approach for developing a distributed multi-agent system for healthcare

This paper presents a service-oriented architecture that allows a more efficient distribution of resources and functionalities. The architecture has been used to develop a multi-agent system aimed at enhancing the assistance and healthcare for Alzheimer patients living in geriatric residences. Most of the system functionalities have been modelled as independent and distributed services, including reasoning, planning and security mechanisms. The results obtained after testing the architecture in a real healthcare scenario demonstrate that a service-oriented approach is far more robust and has better performance than a centralised one

Design of a Predictive Scheduling System to Improve Assisted Living Services for Elders

International audienceAs the number of older adults increases, and with it the demand for dedicated care, geriatric residences face a shortage of caregivers, who themselves experience work overload, stress and burden. We conducted a long-term field study in three geriatric residences to understand the work conditions of caregivers with the aim of developing technologies to assist them in their work and help them deal with their burden. From this study we obtained relevant requirements and insights of design that were used to design, implement and evaluate two prototypes for supporting caregivers' tasks (e.g. electronic recording and automatic notifications), in order to validate the feasibility of their implementation in-situ and the technical requirements. The evaluation in-situ of the prototypes was conducted for a period of four weeks. The results of the evaluation, together with the data collected from six months of use, motivated the design of a predictive schedule. Such design was iteratively improved and evaluated in participative sessions with caregivers. PRESENCE, the predictive schedule we propose, triggers real-time alerts of risky situations (e.g. falls, entering off-limits areas such as the infirmary or the kitchen) and, informs caregivers of routine tasks that need to be performed (e.g. medication administration, diaper change, etc.). Moreover, PRESENCE helps caregivers to record caring tasks (such as diaper changes or medication) and wellbeing assessments (such as the mood), which are difficult to automatize. This facilitates caregiver's shift handover, and can help to train new caregivers by suggesting routine tasks and by sending reminders and timely information about the residents. It can be seen as a tool to reduce the workload of caregivers and medical staff. Instead of trying to substitute the caregiver with an automatic caring system, as proposed by others, we propose the design of our predictive schedule system that blends caregiver's assessments and measurements from sensors. We show the feasibility of predicting caregiver's tasks and a formative evaluation with caregivers that provides preliminary evidence of its utility

Ambient Intelligence Based Architecture for Automated Dynamic Environments.

This paper presents an Ambient Intelligence based architecture that uses intelligent agents with reasoning and planning mechanisms. The agents have the ability to obtain automatic and real time information about the context using a set of technologies, such as radio frequency identification, wireless networks and wireless control devices. The architecture can be implemented on a wide diversity of dynamic environments. A case study is presented, describing the main characteristics of the planning mechanism supported by the architecture, implemented in a geriatric residence, giving the agents a high level of autonomy and flexibility for solving problems

Nature-Inspired Planner Agent for Health Care

This paper presents an autonomous intelligent agent with a human thinking reasoning model, based on past experiences. The agent is developed to assist medical staff in geriatric residences. The health care process is a vital function, requiring nature-inspired solutions imitating the residence staff behaviours. An autonomous deliberative Case-Based Planner agent, AGALZ (Autonomous aGent for monitoring ALZheimer patients), is developed and integrated into an environment-aware multi-agent system, named ALZ-MAS (ALZheimer Multi-Agent System), to optimize health care in geriatric residences. ALZ-MAS is capable of obtaining information about the environment through RFID technology

Ambient Intelligence Agent for Health Care.

This paper presents an autonomous intelligent agent developed for ambient intelligence health care in geriatric residences. The paper focuses on Ambient Intelligence (AmI) Technologies since the vision of AmI assumes seamless, unobtrusive, and often invisible but also controllable interactions between humans and technology. Monitoring within the care process is a vital function requiring AmI solutions. An autonomous deliberative case-based planner agent, AGALZ (Autonomous aGent for monitoring ALZheimer patients), is designed to facilitate the nurses’ integration into a multi-agent intelligent environment, named ALZ-MAS (ALZheimer Multi-Agent System), capable of obtaining information about the environment through RFID technology. The agent operates in wireless devices and is integrated with complementary agents

A Resident-Centered Dementia Care Staff Education Project to Reduce Challenging Behaviors at a Long-Term Care Facility

Frequent use of antipsychotic medication (APM) for behavioral and psychological symptoms of dementia (BPSD) persists at high levels in long- term care (LTC) facilities despite extensive evidence of modest clinical benefits, serious adverse effects, public health advisories and a national initiative to improve dementia care. There is a gap between best-practice evidence and actual clinical practice related to pharmacological and nonpharmacological care for persons with dementia (PWD) and BPSD and/or neuropsychiatric symptoms (NPS) of dementia. The literature shows that clinicians often ignore FDA (Food and Drug Administration) warnings, CMS (the Centers for Medicare and Medicaid Services) initiatives and expert opinion regarding the use of APMs and other psychotropic medications. Surveyed nursing home staff believe pharmacological interventions are more effective than nonpharmacological interventions to manage challenging behaviors. Previous studies document that nonpharmacological interventions and patient/resident-centered education programs are effective in reducing the frequency and severity of BPSD. This project presents an evidence-based interdisciplinary education program developed and administered at a Long Term Care (LTC) facility in the northeast. This program was designed to help staff at long-term care facilities who work with persons with dementia (PWD). This educational intervention project teaches staff a resident-centered approach that enhances care-planning skills for behavior problems and emphasizes meaningful activities to improve the PWD\u27s quality of life, reduce distressing symptoms and decrease the use of psychotropic drugs. This project uses Watson\u27s Theory of Human Caring and integrates several effective patient-centered educational strategies including the STAR-VA program available in the public domain. The STAR-VA program has demonstrated that an intensive interdisciplinary staff education program and development of a behavioral support team can reduce the frequency and intensity of BPSD for PWD. The current project\u27s specific educational program for nurses, nurse managers, certified nursing assistants, activity staff, unit secretaries, and social workers includes five 30-45 minutes sessions. The results demonstrate that an education project can be implemented in a LTC facility to heighten awareness and help staff consider the use of meaningful individualized activities to decrease BPSD. Recommendations include the continued testing of the modified STAR-VA program in long-term care facilities with dissemination to assist staff in working with PWD to reduce BPSD with a nonpharmacological approach. Frequent use of antipsychotic medication (APM) for behavioral and psychological symptoms of dementia (BPSD) persists at high levels in long- term care (LTC) facilities despite extensive evidence of modest clinical benefits, serious adverse effects, public health advisories and a national initiative to improve dementia care. There is a gap between best-practice evidence and actual clinical practice related to pharmacological and nonpharmacological care for persons with dementia (PWD) and BPSD and/or neuropsychiatric symptoms (NPS) of dementia. The literature shows that clinicians often ignore FDA (Food and Drug Administration) warnings, CMS (the Centers for Medicare and Medicaid Services) initiatives and expert opinion regarding the use of APMs and other psychotropic medications. Surveyed nursing home staff believe pharmacological interventions are more effective than nonpharmacological interventions to manage challenging behaviors. Previous studies document that nonpharmacological interventions and patient/resident-centered education programs are effective in reducing the frequency and severity of BPSD. This project presents an evidence-based interdisciplinary education program developed and administered at a Long Term Care (LTC) facility in the northeast. This program was designed to help staff at long-term care facilities who work with persons with dementia (PWD). This educational intervention project teaches staff a resident-centered approach that enhances care-planning skills for behavior problems and emphasizes meaningful activities to improve the PWD\u27s quality of life, reduce distressing symptoms and decrease the use of psychotropic drugs. This project uses Watson\u27s Theory of Human Caring and integrates several effective patient-centered educational strategies including the STAR-VA program available in the public domain. The STAR-VA program has demonstrated that an intensive interdisciplinary staff education program and development of a behavioral support team can reduce the frequency and intensity of BPSD for PWD. The current project\u27s specific educational program for nurses, nurse managers, certified nursing assistants, activity staff, unit secretaries, and social workers includes five 30-45 minutes sessions. The results demonstrate that an education project can be implemented in a LTC facility to heighten awareness and help staff consider the use of meaningful individualized activities to decrease BPSD. Recommendations include the continued testing of the modified STAR-VA program in long-term care facilities with dissemination to assist staff in working with PWD to reduce BPSD with a nonpharmacological approach