Features based proximity localization with Bluetooth emitters

Bouchard, Kévin; Ramezani, Ramin; Naeim, Arash

doi:10.1109/uemcon.2016.7777845

Cited by 18 publications

(17 citation statements)

References 13 publications

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“…Moreover, tracking individuals’ personalized behavioral patterns may allow for the creation of actionable messages to patients and caregivers to improve patient health and outcomes [10]. The purpose of this study was to investigate the physical activity and indoor localization features obtained from our remote patient monitoring system, Sensing At-Risk Population (SARP) [2,11-14]. This study reports on SARP sensor–based markers for rehabilitation screening within a geriatric population, exploring if SARP can be used to prospectively distinguish between at-risk patients in a subacute rehabilitation environment.…”

Section: Introductionmentioning

confidence: 99%

A Combination of Indoor Localization and Wearable Sensor–Based Physical Activity Recognition to Assess Older Patients Undergoing Subacute Rehabilitation: Baseline Study Results

Ramezani¹,

Zhang²,

Xie³

et al. 2019

JMIR Mhealth Uhealth

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Background Health care, in recent years, has made great leaps in integrating wireless technology into traditional models of care. The availability of ubiquitous devices such as wearable sensors has enabled researchers to collect voluminous datasets and harness them in a wide range of health care topics. One of the goals of using on-body wearable sensors has been to study and analyze human activity and functional patterns, thereby predicting harmful outcomes such as falls. It can also be used to track precise individual movements to form personalized behavioral patterns, to standardize the concept of frailty, well-being/independence, etc. Most wearable devices such as activity trackers and smartwatches are equipped with low-cost embedded sensors that can provide users with health statistics. In addition to wearable devices, Bluetooth low-energy sensors known as BLE beacons have gained traction among researchers in ambient intelligence domain. The low cost and durability of newer versions have made BLE beacons feasible gadgets to yield indoor localization data, an adjunct feature in human activity recognition. In the studies by Moatamed et al and the patent application by Ramezani et al, we introduced a generic framework (Sensing At-Risk Population) that draws on the classification of human movements using a 3-axial accelerometer and extracting indoor localization using BLE beacons, in concert. Objective The study aimed to examine the ability of combination of physical activity and indoor location features, extracted at baseline, on a cohort of 154 rehabilitation-dwelling patients to discriminate between subacute care patients who are re-admitted to the hospital versus the patients who are able to stay in a community setting. Methods We analyzed physical activity sensor features to assess activity time and intensity. We also analyzed activities with regard to indoor localization. Chi-square and Kruskal-Wallis tests were used to compare demographic variables and sensor feature variables in outcome groups. Random forests were used to build predictive models based on the most significant features. Results Standing time percentage ( P <.001, d =1.51), laying down time percentage ( P <.001, d =1.35), resident room energy intensity ( P <.001, d =1.25), resident bed energy intensity ( P <.001, d =1.23), and energy percentage of active state ( P =.001, d =1.24) are the 5 most statistically significant features in distinguishing outcome groups at baseline. The energy intensity of the resident room ( P <.001, d =1.25) was achieved by capturing indoor localization information. Random forests revealed that...

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Section: Introductionmentioning

confidence: 99%

A Combination of Indoor Localization and Wearable Sensor–Based Physical Activity Recognition to Assess Older Patients Undergoing Subacute Rehabilitation: Baseline Study Results

Ramezani¹,

Zhang²,

Xie³

et al. 2019

JMIR Mhealth Uhealth

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“…It is also known that for the 2.4 GHz networks, closer distances to an emitter correlate to higher variance in reported RSS. It has also been stated that closer distances to a beacon correlate to a lower detection delays [41]. Table 3 shows the results of exploring the presence of the latter correlation for the A5 smartphone.…”

Section: Environment and Device: Signal Intensities And Advertisementmentioning

confidence: 92%

“…The radio signals in indoor environments are known to be affected by factors like multi-path, fast fading [39], and in the case of 2.4 GHz frequencies, strong human body absorption, which may account for up to ≈10 dBm [40], being even more notable for devices like smartwatches [41]. In addition, the BLE advertisements are broadcast on three narrow (2 MHz width) advertising channels in quick succession, which made the reported signal instability a higher challenge than in Wi-Fi positioning [11].…”

Section: Setup and Collection Proceduresmentioning

confidence: 99%

BLE RSS Measurements Dataset for Research on Accurate Indoor Positioning

Mendoza-Silva

Matey-Sanz

Torres-Sospedra

et al. 2019

Data

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RSS-based indoor positioning is a consolidated research field for which several techniques have been proposed. Among them, Bluetooth Low Energy (BLE) beacons are a popular option for practical applications. This paper presents a new BLE RSS database that was created to aid in the development of new BLE RSS-based positioning methods and to encourage their reproducibility and comparability. The measurements were collected in two university zones: an area among bookshelves in a library and an area of an office space. Each zone had its own batch of deployed iBKS 105 beacons, configured to broadcast advertisements every 200 ms. The collection in the library zone was performed using three Android smartphones of different brands and models, with beacons broadcasting at −12 dBm transmission power, while in the other zone the collection was performed using of one those smartphones with beacons configured to advertise at the −4 dBm, −12 dBm and −20 dBm transmission powers. Supporting materials and scripts are provided along with the database, which annotate the BLE readings, provide details on the collection, the environment, and the BLE beacon deployments, ease the database usage, and introduce the reader to BLE RSS-based positioning and its challenges. The BLE RSS database and its supporting materials are available at the Zenodo repository under the open-source MIT license.

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“…These physical characteristics contribute to another advantage of iBeacons: they are convenient and portable. Furthermore, a typical BLE chip with consistent broadcast intervals of 500 milliseconds consumes very little energy, and requires at most one battery replacement every year, making them extremely reliable under most circumstances [7].…”

Section: Qualities Of An Ibeaconmentioning

confidence: 99%

A Bluetooth-based Proximity Sensing and Object-tracking System

MikeQu¹,

Lu²,

Sun³

2019

8th International Conference on Natural Language Processing (NLP 2019)

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This paper proposes the concept overall concept of a bluetooth-based proximity IoT device. Its methodology is introduced along with a working prototype. Potential applications and viability for data analysis is also discussed. In summary, such a device accomplishes the goal of closerange information communication in an effective, secure and reliable way through the use of beacons utilizing the BLE (Bluetooth Low Energy) Technology, a variety of different receiver devices that has native support for Bluetooth as well as a database used for data storage and retrieval. The biggest advantage of this technology is that proximity-based Internet has virtually endless potential for applications in the real world, including healthcare, retail and industrial manufacturing.

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Features based proximity localization with Bluetooth emitters

Cited by 18 publications

References 13 publications

A Combination of Indoor Localization and Wearable Sensor–Based Physical Activity Recognition to Assess Older Patients Undergoing Subacute Rehabilitation: Baseline Study Results

A Combination of Indoor Localization and Wearable Sensor–Based Physical Activity Recognition to Assess Older Patients Undergoing Subacute Rehabilitation: Baseline Study Results

BLE RSS Measurements Dataset for Research on Accurate Indoor Positioning

A Bluetooth-based Proximity Sensing and Object-tracking System

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