Health – BeaconZone Blog

Using Beacons to Understand Social Drinking

A new study Detecting and Understanding Social Influence During Drinking Situations: Protocol for a Bluetooth-Based Sensor Feasibility and Acceptability, from Brown University United States, evaluates the feasibility and acceptability of using Bluetooth beacons and a smartphone app to measure social interactions in real-world drinking situations among young adults. The background of the study highlights that high-risk drinking often occurs in social settings among peers and the objective was to explore how Bluetooth-based sensors could detect real-time social interactions during drinking events. This data could then inform just-in-time interventions to mitigate risky behaviours.

Participants in the study included 20 young adults who engage in heavy social drinking. Each participant was asked to recruit three friends to carry Bluetooth beacons. These beacons emitted Bluetooth signals detectable by the participants’ smartphones, and a specialised smartphone app triggered reports based on the proximity of these beacons. The data collection was facilitated through Ecological Momentary Assessment (EMA), which involved random, signal-contingent, and morning reports to gather information on alcohol use and social interactions. Reports were triggered when a beacon came within 15 feet of a participant for at least 15 minutes.

During the EMA protocol, participants completed different types of reports. Signal-contingent reports were triggered by the app when a peer’s beacon was detected nearby. Random reports were issued three times daily at random intervals to capture spontaneous interactions and behaviours. Morning reports collected daily data on the previous day’s activities and first-drink reports were initiated by participants when they began drinking.

The implications of the study’s findings are significant. They could inform the development of interventions that provide real-time feedback and support to individuals in high-risk drinking situations, potentially reducing alcohol-related harms. The use of passive sensing technology, such as Bluetooth beacons, enhances the effectiveness of just-in-time interventions by accurately detecting social contexts that influence drinking behaviour.

Enhancing Behavioral Health Monitoring Through Bluetooth Proximity Detection

New research by researchers from Department of Behavioural and Social Sciences Brown University, USA looks into A Bluetooth-Based Smartphone App for Detecting Peer Proximity: Protocol for Evaluating Functionality and Validity.

The study describes a Bluetooth-based smartphone app designed to detect the physical proximity of peers, particularly to monitor health behaviours like alcohol consumption. The app uses Bluetooth beacons and aims to improve upon traditional Ecological Momentary Assessment (EMA) by reducing reliance on participant self-reporting through the passive detection of social interactions.

The primary objective is to develop and validate a system using Bluetooth beacons to passively detect when two or more individuals are in close proximity. The methodology involves 20 participants aged 18-29 years, using a smartphone app to collect data over three weeks. Participants’ influential peers carry Bluetooth beacons, and the app records when beacons come into proximity.

The technology could have significant applications in monitoring and intervening in health behaviours by providing real-time, accurate data on social interactions that influence these behaviours. This could be particularly useful in developing “just-in-time” adaptive interventions targeted at high-risk behaviours as they occur.

Results from the study are expected to be reported by 2025, with potential implications for enhancing the accuracy and efficacy of behavioural health interventions. The technology and methodology developed could be applicable to a broader range of behaviours and settings where social context plays a critical role in health outcomes.

Inovalon Uses Bluetooth iBeacons

Inovalon is a leading provider of cloud-based software solutions focused on data-driven healthcare. Their Inovalon ONE® Platform integrates national-scale connectivity, real-time primary source data access and advanced analytics to improve clinical outcomes and economics across the healthcare ecosystem. It is used by over 20,000 customers, informed by data from more than 78 billion medical events.

The platform uses Bluetooth beacons as part of its healthcare time and attendance management system. These beacons help in accurately tracking employee attendance and location within healthcare facilities, ensuring efficient workforce management. For more details, visit Inovalon’s website.

Enhancing Indoor Localisation for Ambient Assisted Living

New research Simplified Indoor Localisation Using Bluetooth Beacons and Received Signal Strength (RSSI) Fingerprinting with Smartwatch, introduces an innovative system for indoor localisation using Bluetooth Low Energy beacons and smartwatches, aimed at simplifying the process for users. This system is designed to detect a user’s location within specific areas like rooms within a house, rather than providing exact coordinates, with a particular focus on applications in ambient assisted living, especially for the elderly.

The study presents the methodology, implementation, and evaluation of the system, highlighting its practicality for real-world applications. The system demonstrated high accuracy, achieving 92.1% in environments with five rooms and 85.9% with three rooms, showcasing its effectiveness. The setup process is streamlined to reduce the number of reference points and employs a straightforward nearest neighbour algorithm, which simplifies the use and maintenance for users who may not have extensive technical skills.

The use of common and low-cost hardware components, such as Raspberry Pi for beacons and commercial smartwatches, helps keep the system affordable and simple to manage. Calibration is quick and efficient, which is ideal for residential settings. Despite its current effectiveness, the research suggests there is room for improvement. Future enhancements might include the adoption of multiple reference points per region to refine accuracy, particularly in transitional spaces between rooms.

This system offers a robust solution for indoor localisation with significant implications for healthcare, particularly aiding elderly individuals to live independently while ensuring their safety and mobility within their homes.

Indoor Locating Using Beacons in Nursing Care

The new paper Relabeling for Indoor Localization Using Stationary Beacons in Nursing Care Facilities by Christina Garcia and Sozo Inoue from the Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Japan, presents a study on enhancing machine learning for indoor localisation in caregiving, specifically in nursing homes, using Bluetooth Low Energy (BLE) technology.

The study addresses the challenge of limited data available for training machine learning models in indoor localisation, which is critical for monitoring staff-to-patient assistance and managing workload in caregiving environments. The authors propose a data augmentation method that repurposes the Received Signal Strength (RSSI) from various beacons by re-labeling them to locations with fewer data samples, thus resolving data imbalances. This method uses standard deviation and Kullback–Leibler divergence to measure signal patterns and find matching beacons for re-labeling. Two variations of re-labeling are implemented: full and partial matching.

The performance of this method is evaluated using a real-world dataset collected over five days in a nursing care facility equipped with 25 Bluetooth beacons.

Overall, the study highlights the effectiveness of the proposed re-labelling method in enhancing indoor localisation accuracy in nursing care facilities, providing a valuable contribution to the field of caregiving and workload management.

Indoor Tracking of Individuals with Mild Cognitive Impairment

There’s new research from the USA on Indoor Localization using Bluetooth and Inertial Motion Sensors in Distributed Edge and Cloud Computing Environment (PDF). The paper describes a low-cost, scalable, edge computing system for tracking indoor movements in a large indoor facility. The system uses Bluetooth Low Energy (BLE) and Inertial Measurement Unit sensors (IMU) and is designed to facilitate therapeutic activities for individuals with Mild Cognitive Impairment.

The implementation involved instrumenting a facility with 39 edge computing systems and an on-premise fog server. Subjects carried BLE beacon and IMU sensors on-body. The researchers developed an adaptive trilateration approach that considered the temporal density of hits from the BLE beacon to surrounding edge devices to handle inconsistent coverage of edge devices in large spaces with varying signal strength. They also integrated IMU-based tracking methods using a dead-reckoning technique to improve the system’s accuracy.

The conclusions of the study showed that the proposed system could robustly localise the position of multiple people with an average error of 4 meters across the entire study space, also showing 87% accuracy for room-level localisations. The integration of IMU-based dead-reckoning with Bluetooth-based localisation further enhanced the system’s accuracy.

Using Beacons to Mitigate Staff Duress

Staff duress, also known as employee duress or worker duress, is where employees may feel threatened, intimidated, or unsafe while performing their job duties. This can occur in a variety of industries, including healthcare, education, retail, hospitality, and security.

Problems associated with staff duress include:

Employee safety: If employees feel threatened or unsafe, it can have a negative impact on their well-being, job satisfaction, and productivity.

Employer liability: Employers have a legal obligation to provide a safe working environment for their employees. Failure to do so can result in legal action and financial penalties.

Costly incidents: If an employee is injured due to a safety issue, it can result in costly workers’ compensation claims, lawsuits, and reputational damage to the employer.

Beacons with buttons, used with real time locating systems, can help mitigate staff duress by providing a quick and effective way for employees to signal for help in an emergency situation. These devices have a wearable or handheld button that employees can press to trigger an alert. The alert is then sent to a designated response team, who can quickly assess the situation and provide assistance as needed.

Beacons with buttons can be especially useful in industries where employees work alone or in remote locations. They can also be helpful in schools and universities, where teachers and staff members may be at risk of violence or other safety threats.

Beacons with buttons

Minew B7 In Stock

We now supply the Minew B7 wearable wristband beacon.

This waterproof (IP67) beacon offers the usual iBeacon and Eddystone advertising as well as acceleration sensing. This can be via x y z in the advertising or for motion triggered broadcast. This beacon is also one of the few that also has an NFC chip for additional RFiD-based sensing. The button can be used for on/off as well as button triggered broadcasting in situations such as lone working or SOS.

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W7 Security Beacon

We have the new W7 security beacon in stock, suitable for use in places such as hospitals and prisons. It’s fitted with a security screwdriver and advertises an alert if the wristband is removed or cut off.

The W7 advertises iBeacon and Eddystone as well as acceleration (x y z) and body temperature. It’s waterproof to IP67 and is rechargeable via magnetic USB cable. The battery lasts up to a year on one charge, depending on settings.

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Using Beacons for Disability Location Determination

Researchers in Japan have been using iBeacons with children with PIMD/SMID’s expressive behaviours. These are children with profound intellectual and multiple disabilities or severe motor and intellectual disabilities who can only communicate through movements, vocalizations, body postures, muscle tensions or facial expressions.

The researchers created a system to interpret the expressive behaviours. The system uses the ChildSIDE in app to collect behaviours of children and sends the location and environmental data to a database. The beacons allow the location to be known so that displays or interfaces can be automatically changed depending on the context. For example, a specific situation (e.g. class or playtime), location (e.g. classroom, playground, home) or time (e.g. morning, lunch breaks, evening) can be determined.

ChildSIDE provides an effective method of collecting children’s expressive behaviours with a high accuracy rate in detecting and transmitting environmental and location data.

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