GSA: A Framework for Rapid Prototyping of Smart Alarm Systems

We describe the Generic Smart Alarm, an architectural framework for the development of decision support modules for a variety of clinical applications. The need to quickly process patient vital signs and detect patient health events arises in many clinical scenarios, from clinical decision support to tele-health systems to home-care applications. The events detected during monitoring can be used as caregiver alarms, as triggers for further downstream processing or logging, or as discrete inputs to decision support systems or physiological closed-loop applications. We believe that all of these scenarios are similar, and share a common framework of design. In attempting to solve a particular instance of the problem, that of device alarm fatigue due to numerous false alarms, we devised a modular system based around this framework. This modular design allows us to easily customize the framework to address the specific needs of the various applications, and at the same time enables us to perform checking of consistency of the system. In the paper we discuss potential specific clinical applications of a generic smart alarm framework, present the proposed architecture of such a framework, and motivate the benefits of a generic framework for the development of new smart alarm or clinical decision support systems

Discovering human activities from binary data in smart homes

With the rapid development in sensing technology, data mining, and machine learning fields for human health monitoring, it became possible to enable monitoring of personal motion and vital signs in a manner that minimizes the disruption of an individual’s daily routine and assist individuals with difficulties to live independently at home. A primary difficulty that researchers confront is acquiring an adequate amount of labeled data for model training and validation purposes. Therefore, activity discovery handles the problem that activity labels are not available using approaches based on sequence mining and clustering. In this paper, we introduce an unsupervised method for discovering activities from a network of motion detectors in a smart home setting. First, we present an intra-day clustering algorithm to find frequent sequential patterns within a day. As a second step, we present an inter-day clustering algorithm to find the common frequent patterns between days. Furthermore, we refine the patterns to have more compressed and defined cluster characterizations. Finally, we track the occurrences of various regular routines to monitor the functional health in an individual’s patterns and lifestyle. We evaluate our methods on two public data sets captured in real-life settings from two apartments during seven-month and three-month periods

Patient Status Monitoring For Smarthome Healthcare

The purpose of this project is to create a patient status monitoring system for smart home healthcare. The suggested setup monitors the patient's vital signs and activity levels using wireless sensors and Wi-Fi technologies. The system gathers information from a variety of sensors, including heart rate, concentration of oxygen level and body temperature. The acquired data is subsequently sent to a cloud server for analysis and processing. The analyzed data are used to deliver real-time information on the patient's health state to caregiver and medical experts, which enables immediate actions and medical attention. The system is designed to be easily integrated into the existing smart home infrastructure and is intended to improve the quality of life and health outcomes of the patient’s population in urban areas. All the objectives have been accomplished. Due to a significant inaccuracy, the outcome is, nevertheless, not very precise. The average percentage of inaccuracy for LM 35 was determined to be 4.43%. Meanwhile for MAX30102, which can detect concentration of oxygen level and heart rate have a percentage error of 0.6% and 9.7%

Can vital signs recorded in patients' homes aid decision making in emergency care? A Scoping Review

Aim: Use of tele-health programs and wearable sensors that allow patients to monitor their own vital signs have been expanded in response to COVID-19. We aimed to explore the utility of patient-held data during presentation as medical emergencies. Methods: We undertook a systematic scoping review of two groups of studies: studies using non-invasive vital sign monitoring in patients with chronic diseases aimed at preventing unscheduled reviews in primary care, hospitalization or emergency department visits and studies using vital sign measurements from wearable sensors for decision making by clinicians on presentation of these patients as emergencies. Only studies that described a comparator or control group were included. Studies limited to inpatient use of devices were excluded. Results: The initial search resulted in 896 references for screening, nine more studies were identified through searches of references. 26 studies fulfilled inclusion and exclusion criteria and were further analyzed. The majority of studies were from telehealth programs of patients with congestive heart failure or Chronic Obstructive Pulmonary Disease. There was limited evidence that patient held data is currently used to risk-stratify the admission or discharge process for medical emergencies. Studies that showed impact on mortality or hospital admission rates measured vital signs at least daily. We identified no interventional study using commercially available sensors in watches or smart phones. Conclusions: Further research is needed to determine utility of patient held monitoring devices to guide management of acute medical emergencies at the patients’ home, on presentation to hospital and after discharge back to the community

Healthcare PANs: Personal Area Networks for trauma care and home care

The first hour following the trauma is of crucial importance in trauma care. The sooner treatment begins, the better the ultimate outcome for the patient. Generally the initial treatment is handled by paramedical personnel arriving at the site of the accident with an ambulance. There is evidence to show that if the expertise of the on-site paramedic team can be supported by immediate and continuous access to and communication with the expert medical team at the hospital, patient outcomes can be improved. After care also influences the ultimate recovery of the patient. After-treatment follow up often occurs in-hospital in spite of the fact that care at home can offer more advantages and can accelerate recovery. Based on emerging and future wireless communication technologies, in a previous paper [1] we presented an initial vision of two future healthcare settings, supported by applications which we call Virtual Trauma Team and Virtual Homecare Team. The Virtual Trauma Team application involves high quality wireless multimedia communications between ambulance paramedics and the hospital facilitated by paramedic Body Area Networks (BANs) [2] and an ambulance-based Vehicle Area Network (VAN). The VAN supports bi-directional streaming audio and video communication between the ambulance and the hospital even when moving at speed. The clinical motivation for Virtual Trauma Team is to increase survival rates in trauma care. The Virtual Homecare Team application enables homecare coordinated by home nursing services and supported by the patient's PAN which consists of a patient BAN in combination with an ambient intelligent home environment. The homecare PAN provides intelligent monitoring and support functions and the possibility to ad hoc network to the visiting health professionals’ own BANs as well as high quality multimedia communication links to remote members of the virtual team. The motivation for Virtual Homecare Team is to improve quality of life and independence for patients by supporting care at home; the economic motivation is to replace expensive hospital-based care with homecare by virtual teams using wireless technology to support the patient and the carers. In this paper we develop the vision further and focus in particular on the concepts of personal and body area networks

Design of a contactless body temperature measurement system using arduino

The recent advances in electronics and microelectronics devices allow the development of newly low-cost monitoring tools used by peoples for health preventive purposes. Sensors used in medical equipments convert various forms of human body vital signs into electrical signals. Therefore, the healthcare monitoring systems considering non-invasive and wearable sensors with integrated communication mediums allow an efficient solution to live a comfortable home life. This paper presents the remote monitoring of human body temperature (HBT) wirelessly by means of Arduino controller with different sensors and open source internet connection. The proposed monitoring system uses an internet network via wireless fieldity (wifi) connection to be linked with online portal on smart phone or computer. The proposed system is comprised of an Arduino controller, LM-35 (S1), MLX-90614 (S2) temperature sensors and ESP-wifi shield module. The obtained result has shown that real time temperature monitoring data can be transferred to authentic observer by utilizing internet of things (IoT) applications. The findings from this research indicates that the difference of average temperature in between Sensor S1 and S2 is about 15 0C

Smart nanotextiles: materials and their application

Textiles are ubiquitous to us, enveloping our skin and surroundings. Not only do they provide a protective shield or act as a comforting cocoon but they also serve esthetic appeal and cultural importance. Recent technologies have allowed the traditional functionality of textiles to be extended. Advances in materials science have added intelligence to textiles and created ‘smart’ clothes. Smart textiles can sense and react to environmental conditions or stimuli, e.g., from mechanical, thermal, chemical, electrical, or magnetic sources (Lam Po Tang and Stylios 2006). Such textiles find uses in many applications ranging from military and security to personalized healthcare, hygiene, and entertainment. Smart textiles may be termed ‘‘passive’’ or ‘‘active.’’ A passive smart textile monitors the wearer’s physiology or the environment, e.g., a shirt with in-built thermistors to log body temperature over time. If actuators are integrated, the textile becomes an active, smart textile as it may respond to a particular stimulus, e.g., the temperature-aware shirt may automatically roll up the sleeves when body temperature rises. The fundamental components in any smart textile are sensors and actuators. Interconnections, power supply, and a control unit are also needed to complete the system. All these components must be integrated into textiles while still retaining the usual tactile, flexible, and comfortable properties that we expect from a textile. Adding new functionalities to textiles while still maintaining the look and feel of the fabric is where nanotechnology has a huge impact on the textile industry. This article describes current developments in materials for smart nanotextiles and some of the many applications where these innovative textiles are of great benefit

M-health review: joining up healthcare in a wireless world

In recent years, there has been a huge increase in the use of information and communication technologies (ICT) to deliver health and social care. This trend is bound to continue as providers (whether public or private) strive to deliver better care to more people under conditions of severe budgetary constraint