Dataset from PPG wireless sensor for activity monitoring.
Ontology highlight
ABSTRACT:
SUBMITTER: Biagetti G
PROVIDER: S-EPMC6971339 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:We introduce a dataset to provide insights into the relationship between the diaphragm surface electromyographic (sEMG) signal and the respiratory air flow. The data presented had been originally collected for a research project jointly developed by the Department of Information Engineering and the Department of Industrial Enginering and Mathematical Sciences, Polytechnic University of Marche, Ancona, Italy. This article describes data recorded from 8 subjects, and includes 8 air flow and 8 surface electromyographic (sEMG) signals for diaphragmatic respiratory activity monitoring, measured with a sampling frequency of 2 kHz.
| S-EPMC6698777 | biostudies-literature
Project description:To evaluate continuous monitoring of maternal hemodynamics during labor and delivery utilizing an innovative, noninvasive, reflective photoplethysmography-based device. The Biobeat Monitoring Platform includes a wearable wristwatch monitor that automatically samples cardiac output (CO), blood pressure (BP), stroke volume (SV), systemic vascular resistance (SVR), heart rate (HR) every 5 s and uploads all data to a smartphone-based app and to a data cloud, enabling remote patient monitoring and analysis of data. Low-risk parturients at term, carrying singletons pregnancies, were recruited at early delivery prior to the active phase. Big data analysis of the collected data was performed using the Power BI analysis tool (Microsoft). Next, data were normalized to visual presentation using Excel Data Analysis and the regression tool. Average measurements were compared before and after rupture of membranes, epidural anesthesia, fetal delivery, and placental expulsion. Eighty-one parturients entered analysis. Epidural anesthesia was associated with a slight elevation in CO (5.5 vs. 5.6, L/min, 10 min before and after EA, p <0.05) attributed to a non-significant increase in both HR and SV. BP remained stable as of counter decrease in SVR (1361 vs. 1319 mmHg⋅min⋅mL-1, 10 min before and after EA, p <0.05). Fetal delivery was associated with a peak in CO after which it rapidly declined (6.0 vs. 7.2 vs. 6.1 L/min, 30 min before vs. point of delivery vs. after delivery, p <0.05). The mean BP remained stable throughout delivery with a slight increase at fetal delivery (92 vs. 95 vs. 92.1 mmHg, p <0.05), reflecting the increase in CO and decrease in SVR (1284 vs. 1112 vs. 1280 mmHg⋅min⋅mL-1,p <0.05)with delivery. Placental expulsion was associated with a second peak in CO and decrease in SVR. We presented a novel application of noninvasive hemodynamic maternal monitoring throughout labor and delivery for both research and clinical use.
| S-EPMC7793094 | biostudies-literature
Project description:This paper presents the collected experimental data for water quality monitoring which was conducted in ten experiments by using five different common sources of water contaminants namely soil, salt, washing powder, chlorine and vinegar and their combination. The data were collected indoors at room temperature during the day for several days using sensors that measure pH, turbidity, flow rate, and conductivity in water. The water consumption risk (CR) was calculated as deviation based on the water quality parameters standards proposed by the World Health Organisation (WHO) and the South African Department of Water Affairs (DWA), with respect to the sensor measurement readings obtained. While the error measurements were calculated based on the expected parameter measurement per conducted experiment and repeated for 26 measurements. Pure tap water was the benchmark of water safe for human consumption. The first five experiments were performed by introducing each contaminant into the water and thereafter, two contaminants in the sixth experiment and their additions until all different contaminants were experimented at once in the last experiment.
| S-EPMC6879973 | biostudies-literature
Project description:This dataset was collected as part of the InWaterSense project with a wireless sensor network (WSN) installed in a site in river Sitnica in Kosovo, as a case study for monitoring remotely, continuously and in real-time the surface water quality in Kosovo and how it can be extended to all surface waters in the country for quality assurance. Values of four water quality parameters are provided in the dataset, i.e., temperature, electrical conductivity, pH, and dissolved oxygen measured by respective static sensors of WSN in the time frame between May 2015 to beginning of January 2016 and every 10 min, counting to slightly over 100k measurement records in total. The dataset is hosted at the Mendeley Data repository (Ahmedi and Ahmedi 2021), and is related to the research article entitled "InWaterSense: An Intelligent Wireless Sensor Network for Monitoring Surface Water Quality to a River in Kosovo" (Ahmedi et al., 2018). The reuse potential of the dataset to the scientific community is widespread, from environmental engineering to artificial intelligence to the health sector just to mention few. Moreover, practitioners might benefit from this dataset in driving forth the pollution prevention policies and techniques. Data were acquired measuring water quality using static sensors installed as part of a wireless sensor network in Sitnica river in the Plemetin village near Prishtina, then transmitted to the gateway device also in Plemetin via the ZigBee protocol, and finally transmitted remotely via GPRS to the server machine in the premises of the University of Prishtina. The data received from sensors are in real-time stored in the MS SQL server.
| S-EPMC9382137 | biostudies-literature
Project description:A wristwatch-based wireless sensor platform for IoT wearable health monitoring applications is presented. The paper describes the platform in detail, with a particular focus given to the design of a novel and compact wireless sub-system for 868 MHz wristwatch applications. An example application using the developed platform is discussed for arterial oxygen saturation (SpO2) and heart rate measurement using optical photoplethysmography (PPG). A comparison of the wireless performance in the 868 MHz and the 2.45 GHz bands is performed. Another contribution of this work is the development of a highly integrated 868 MHz antenna. The antenna structure is printed on the surface of a wristwatch enclosure using laser direct structuring (LDS) technology. At 868 MHz, a low specific absorption rate (SAR) of less than 0.1% of the maximum permissible limit in the simulation is demonstrated. The measured on-body prototype antenna exhibits a -10 dB impedance bandwidth of 36 MHz, a peak realized gain of -4.86 dBi and a radiation efficiency of 14.53% at 868 MHz. To evaluate the performance of the developed 868 MHz sensor platform, the wireless communication range measurements are performed in an indoor environment and compared with a commercial Bluetooth wristwatch device.
| S-EPMC7147171 | biostudies-literature
Project description:ObjectiveRecording seizures using personal seizure diaries can be challenging during everyday life and many seizures are missed or mis-reported. People living with epilepsy could benefit by having a more accurate and objective wearable EEG system for counting seizures that can be used outside of the hospital. The objective of this study was to (1) determine which seizure types can be electrographically recorded from the scalp below the hairline, (2) determine epileptologists' ability to identify electrographic seizures from single-channels extracted from full-montage wired-EEG, and (3) determine epileptologists' ability to identify electrographic seizures from Epilog, a wireless single-channel EEG sensor.MethodsEpilog sensors were worn concurrently during epilepsy monitoring unit (EMU) monitoring. During standard-of-care review, epileptologists were asked if the electrographic portion of the seizure was visible on single channels of wired electrodes at locations proximal to Epilog sensors, and if focal-onset, which electrode was closest to the focus. From these locations, single channels of EEG extracted from wired full-montage EEG and the proximal Epilog sensor were presented to 3 blinded epileptologists along with markers for when known seizures occurred (taken from the standard-of-care review). Control segments at inter-ictal times were included as control. The epileptologists were asked whether a seizure event was visible in the single channel EEG record at or near the marker.ResultsA total of 75 seizures were recorded from 22 of 40 adults that wore Epilog during their visit to the EMU. Epileptologists were able to visualize known seizure activity on at least one of the wired electrodes proximal to Epilog sensors for all seizure events. Epileptologists accurately identified seizures in 71% of Epilog recordings and 84% of single-channel wired recordings and were 92% accurate identifying seizures with Epilog when those seizures ended in a clinical convulsion compared to those that did not (>55%).ConclusionsEpileptologists are able to visualize seizure activity on single-channels of EEG at locations where Epilog sensors are easily placed on the scalp below hairline. Manual review of seizure annotations can be done quickly and accurately (>70% TP and >98% PPV) on single-channel EEG data. Reviewing single-channel EEG is more accurate than what has been reported in the literature on self-reporting seizures in seizure diaries, the current standard of care for seizure counting outside of the EMU.SignificanceWearable EEG will be important for seizure monitoring outside of the hospital. Epileptologists can accurately identify seizures in single-channel EEG, better than patient self-reporting in diaries based on the literature. Automated or semi-automated seizure detection on single channels of EEG could be used in the future to objectively count seizures to complement the standard of care outside of the EMU without the overt burden upon epileptologist review.
| S-EPMC8220094 | biostudies-literature
Project description:To the best of our knowledge, there is no annotated database of PPG signals recorded by smartphone publicly available. This article introduces Brno University of Technology Smartphone PPG Database (BUT PPG) which is an original database created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology, for the purpose of evaluating photoplethysmographic (PPG) signal quality and estimation of heart rate (HR). The data comprises 48 10-second recordings of PPGs and associated electrocardiographic (ECG) signals used for determination of reference HR. The data were collected from 12 subjects (6 female, 6 male) aged between 21 and 61. PPG data were collected by smartphone Xiaomi Mi9 with sampling frequency of 30 Hz. Reference ECG signals were recorded using a mobile ECG recorder (Bittium Faros 360) with a sampling frequency of 1,000 Hz. Each PPG signal includes annotation of quality created manually by biomedical experts and reference HR. PPG signal quality is indicated binary: 1 indicates good quality for HR estimation, 0 indicates signals where HR cannot be detected reliably, and thus, these signals are unsuitable for further analysis. As the only available database containing PPG signals recorded by smartphone, BUT PPG is a unique tool for the development of smart, user-friendly, cheap, on-the-spot, self-home-monitoring of heart rate with the potential of widespread using.
| S-EPMC8440059 | biostudies-literature
Project description:Through harvesting energy by wireless charging and delivering data by wireless communication, this study proposes the concept of a wireless sensor enabled by wireless power (WPWS) and reports the fabrication of a prototype for functional tests. One WPWS node consists of wireless power module and sensor module with different chip-type sensors. Its main feature is the dual antenna structure. Following RFID system architecture, a power harvesting antenna was designed to gather power from a standard reader working in the 915 MHz band. Referring to the Modbus protocol, the other wireless communication antenna was integrated on a node to send sensor data in parallel. The dual antenna structure integrates both the advantages of an RFID system and a wireless sensor. Using a standard UHF RFID reader, WPWS can be enabled in a distributed area with a diameter up to 4 m. Working status is similar to that of a passive tag, except that a tag can only be queried statically, while the WPWS can send dynamic data from the sensors. The function is the same as a wireless sensor node. Different WPWSs equipped with temperature and humidity, optical and airflow velocity sensors are tested in this study. All sensors can send back detection data within 8 s. The accuracy is within 8% deviation compared with laboratory equipment. A wireless sensor network enabled by wireless power should be a totally wireless sensor network using WPWS. However, distributed WPWSs only can form a star topology, the simplest topology for constructing a sensor network. Because of shielding effects, it is difficult to apply other complex topologies. Despite this limitation, WPWS still can be used to extend sensor network applications in hazardous environments. Further research is needed to improve WPWS to realize a totally wireless sensor network.
| S-EPMC3571774 | biostudies-literature
Project description:An important aspect of eye health in humans and animal models of human diseases is intraocular pressure (IOP). IOP is typically measured by hand with a tonometer, so data are sparse and sporadic and round-the-clock variations are not well characterized. Here we present a novel system for continuous wireless IOP and temperature measurement in small animals. The system consists of a cannula implanted in the anterior chamber of the eye connected to pressure sensing electronics that can be worn by rats or implanted in larger mammals. The system can record IOP with 0.3 mmHg accuracy and negligible drift at a rate of 0.25 Hz for 1-2 months on a regulated battery or indefinitely at rates up to 250 Hz via RF energy harvesting. Chronic recordings from conscious rats showed that IOP follows a diurnal rhythm, averaging 16.5 mmHg during the day and 21.7 mmHg at night, and that the IOP rhythm lags a diurnal rhythm in body temperature by 2.1 h. IOP and body temperature fluctuations were positively correlated from moment-to-moment as well. This technology allows researchers to monitor for the first time the precise IOP history of rat eyes, a popular model for glaucoma studies.
| S-EPMC7034622 | biostudies-literature
Project description:Autonomous liquid-volume monitoring is crucial in ubiquitous healthcare. However, conventional approach is based on either human visual observation or expensive detectors, which are costly for future pervasive monitoring. Here we introduce a novel approach based on passive harmonic transponder antenna sensor and frequency hopping spread spectrum (FHSS) pattern analysis, to provide a very low cost wireless ?L-resolution liquid-volume monitoring without battery or digital circuits. In our conceptual demonstration, the harmonic transponder comprises of a passive nonlinear frequency multiplier connected to a metamaterial-inspired 3-D antenna designed to be highly sensitive to the liquid-volume within a confined region. The transponder first receives some FHSS signal from an interrogator, then converts such signal to its harmonic band and re-radiates through the antenna sensor. The harmonic signal is picked up by a sniffer receiver and decoded through pattern analysis of the high dimensional FHSS signal strength data. A robust, zero power, absolute accuracy wireless liquid-volume monitoring is realized in the presence of strong direct coupling, background scatters, distance variance as well as near-field human-body interference. The concepts of passive harmonic transponder sensor, metamaterial-inspired antenna sensor, and FHSS pattern analysis based sensor decoding may help establishing cost-effective, energy-efficient and intelligent wireless pervasive healthcare monitoring platforms.
| S-EPMC4702130 | biostudies-literature