Collaborative processing of wearable and ambient sensor system for blood pressure monitoring

A novel diversity method for smartphone camera-based heart rhythm signals in the presence of motion and noise artifacts

The advent of smartphones has advanced the use of embedded sensors to acquire various physiological information. For example, smartphone camera sensors and accelerometers can provide heart rhythm signals to the subjects, while microphones can give respiratory signals. However, the acquired smartphone-based physiological signals are more vulnerable to motion and noise artifacts (MNAs) compared to using medical devices, since subjects need to hold the smartphone with proper contact to the smartphone camera and lens stably and tightly for a duration of time without any movement in the hand or finger. This results in more MNA than traditional methods, such as placing a finger inside a tightly enclosed pulse oximeter to get PPG signals, which provides stable contact between the sensor and the subject's finger. Moreover, a smartphone lens does not block ambient light in an effective way, while pulse oximeters are designed to block the ambient light effectively. In this paper, we propose a novel diversity method for smartphone signals that reduces the effect of MNAs during heart rhythm signal detection by 1) acquiring two heterogeneous signals from a color intensity signal and a fingertip movement signal, and 2) selecting the less MNA-corrupted signal of the two signals. The proposed method has advantages in that 1) diversity gain can be obtained from the two heterogeneous signals when one signal is clean while the other signal is corrupted, and 2) acquisition of the two heterogeneous signals does not double the acquisition procedure but maintains a single acquisition procedure, since two heterogeneous signals can be obtained from a single smartphone camera recording. In our diversity method, we propose to choose the better signal based on the signal quality indices (SQIs), i.e., standard deviation of instantaneous heart rate (STD-HR), root mean square of the successive differences of peak-to-peak time intervals (RMSSD-T), and standard deviation of peak values (STD-PV). As a performance metric evaluating the proposed diversity method, the ratio of usable period is considered. Experimental results show that our diversity method increases the usable period 19.53% and 6.25% compared to the color intensity or the fingertip movement signals only, respectively.

Wearable glove sensor for non-invasive organophosphorus pesticide detection based on a double-signal fluorescence strategy

A wearable glove-based sensor has been developed for non-invasive organophosphorus pesticide (OP) monitoring via the fluorescent detection technology. The new "lab-on-a-glove" device integrates a flexible host material (CMC aerogel) and two fluorescent centers (EuMOFs for red and nanosized CDs for blue emissons). After characterizing the performance and stability of the sensor, qualitative and quantitative OP detections are successfully conducted on the surfaces of different agricultural products using swipe collection. The real-time detection system offers considerable advantages such as rapid response (30 s) due to the porous structures of CMC aerogel and MOFs, detection with the naked eye (the red to blue emission transition corresponds to an increase in the OP concentration) and high sensitivity (R2 = 0.99529, LOD = 89 nM) owing to the double-signal sensing strategy in which EuMOFs are the working fluorescence center and CDs are the reference fluorescence center. Compared with other OP detection methods, our strategy of using wearable device with the ratiometric fluorescence method leads to a convenient and reliable detection process for OP analysis. Also, considering its cost advantage, the glove-based sensor holds promise for practical applications in food safety and security.

Trial of real-time locating and messaging system with Bluetooth low energy

BACKGROUND

Hospital real-time location systems (RTLS) are increasing efficiency and reducing operational costs, but room access tags are necessary.

OBJECTVE

We developed three iPhone 5 applications for an RTLS and communications using Bluetooth low energy (BLE).

METHODS

The applications were: Peripheral device tags, Central beacons, and a Monitor. A Peripheral communicated with a Central using BLE. The Central communicated with a Monitor using sockets on TCP/IP (Transmission Control Protocol/Internet Protocol) via a WLAN (wireless local area network). To determine a BLE threshold level for the received signal strength indicator (RSSI), relationships between signal strength and distance were measured in our laboratory and on the terrace.

RESULTS

The BLE RSSI threshold was set at -70 dB, about 10 m. While an individual with a Peripheral moved around in a concrete building, the Peripheral was captured in a few 10-sec units at about 10 m from a Central. The Central and Monitor showed and saved the approach events, location, and Peripheral's nickname sequentially in real time. Remote Centrals also interactively communicate with Peripherals by intermediating through Monitors that found the nickname in the event database.

CONCLUSIONS

Trial applications using BLE on iPhones worked well for patient tracking, and messaging in indoor environments.

Synchronization in wireless biomedical-sensor networks with Bluetooth Low Energy

Bluetooth Low Energy (BLE) has reduced the energy consumption for sensor nodes drastically. One major reason for this improvement is a non-continuous connection between the nodes. But this causes also a nondeterministic data transmission time. Most synchronization protocols are influenced by this characteristic, with the result of less accuracy. In wireless body sensor networks this accuracy is often of vital importance. Therefore this paper evaluates different synchronization principles customized for BLE.

For the evaluation measurements we used two BLE modules connected to one micro controller. This setup allowed us to calculate the error directly for the different principles. First we measured the send-receive time as a reference which influences most synchronization protocols. This time is directly affected by random transmission delays of BLE. Second we used the time difference between receiving and acknowledging a message as principle (A). The last principle (B) can only be used between nodes that use BLE that don’t require a constant connection, because it needs to connect and disconnect the nodes. After a new connection the “connected” events occur in the BLE nodes almost at the same time and can be used for synchronization. The reference measurement showed the worst results. The average delay was 4.76 ms with a standard deviation of 2.32 ms. Principle (A) showed average delays of 7.51 ms, which was almost exactly 1 connection interval in our setup. The standard deviation was 0.41 ms. Principle (B) showed the best results with an average time difference of 39.92 μs and a standard deviation of 14.19 μs

The results showed that with the principles (A) and (B) the synchronization of nodes can be highly improved compared to the reference. In future we will test the principles with synchronization protocols in real sensor nodes also with respect to the processor load.

Overview and Evaluation of Bluetooth Low Energy: An Emerging Low-Power Wireless Technology

Bluetooth Low Energy (BLE) is an emerging low-power wireless technology developed for short-range control and monitoring applications that is expected to be incorporated into billions of devices in the next few years. This paper describes the main features of BLE, explores its potential applications, and investigates the impact of various critical parameters on its performance. BLE represents a trade-off between energy consumption, latency, piconet size, and throughput that mainly depends on parameters such as connInterval and connSlaveLatency. According to theoretical results, the lifetime of a BLE device powered by a coin cell battery ranges between 2.0 days and 14.1 years. The number of simultaneous slaves per master ranges between 2 and 5,917. The minimum latency for a master to obtain a sensor reading is 676 μs, although simulation results show that, under high bit error rate, average latency increases by up to three orders of magnitude. The paper provides experimental results that complement the theoretical and simulation findings, and indicates implementation constraints that may reduce BLE performance.