Harinath Garudadri

An Ultra Low Power Pulse Oximeter Sensor Based on Compressed Sensing

We describe an ultra low power pulse oximeter sensor for long term, non-invasive monitoring of SpO2 and heart rate in Body Area Networks (BAN). Commercial pulse oximeter sensors consume about 20-60 mW of power during continuous operation. Other researchers have shown that accurate and noise robust wireless pulse oximeter sensors can be designed to operate with as little as 1.5 mW. The LEDs consume bulk of the power budget in pulse oximeter sensors. In this work, we describe a compressed sensing approach to sample the photodetector output, so that the LEDs can be turned off for longer periods and thus save sensor power. We randomly sample Photoplethysmogram (PPG) signals with about 10-40x fewer samples than with uniform sampling and demonstrate that the accuracy of heart rate estimation and blood pressure estimation are not compromised, using MIMIC database. This provides power savings of the order of 10-40x for a pulse oximeter sensor, by reducing the duration LEDs need to be turned on.

Noninvasive Cuffless Estimation of Blood Pressure from Pulse Arrival Time and Heart Rate with Adaptive Calibration

We study the problem of noninvasively estimating Blood Pressure (BP) without using a cuff, which is attractive for continuous monitoring of BP over Body Area Networks. It has been shown that the Pulse Arrival Time (PAT) measured as the delay between the ECG peak and a point in the finger PPG waveform can be used to estimate systolic and diastolic BP. Our aim is to evaluate the performance of such a method using the available MIMIC database, while at the same time improve the performance of existing techniques. We propose an algorithm to estimate BP from a combination of PAT and heart rate, showing improvement over PAT alone. We also show how the method achieves recalibration using an RLS adaptive algorithm. Finally, we address the use case of ECG and PPG sensors wirelessly communicating to an aggregator and study the effect of skew and jitter on BP estimation.

Video transport over wireless networks

In this paper, we propose an efficient scheme to transport video over wireless networks, specifically cdma2000® 1x. Speech transmission over cdma2000® uses a variable rate voice coder (vocoder) over a channel with multiple fixed rates. We apply these ideas to compressed video transmission over wireless IP networks. Explicit Bit Rate (EBR) video compression is designed to match the video encoder output to a set of fixed channel rates. We show that in comparison with VBR video transmission over a fixed rate wireless channel, EBR video transmission provides improved error resilience, reduced latency and improved efficiency.

Multistream network feature processing for a distributed speech recognition system

A distributed voice recognition system and method for obtaining acoustic features and speech activity at multiple frequencies by extracting high frequency components thereof on a device, such as a subscriber station and transmitting them to a network server having multiple stream processing capability, including cepstral feature processing, MLP nonlinear transformation processing, and multiband temporal pattern architecture processing. The features received at the network server are processed using all three streams, wherein each of the three streams provide benefits not available in the other two, thereby enhancing feature interpretation. Feature extraction and feature interpretation may operate at multiple frequencies, including but not limited to 8 kHz, 11 kHz, and 16 kHz.

Packet loss mitigation for biomedical signals in healthcare telemetry

In this work, we propose an effective application layer solution for packet loss mitigation in the context of Body Sensor Networks (BSN) and healthcare telemetry. Packet losses occur due to many reasons including excessive path loss, interference from other wireless systems, handoffs, congestion, system loading, etc. A call for action is in order, as packet losses can have extremely adverse impact on many healthcare applications relying on BAN and WAN technologies. Our approach for packet loss mitigation is based on Compressed Sensing (CS), an emerging signal processing concept, wherein significantly fewer sensor measurements than that suggested by Shannon/Nyquist sampling theorem can be used to recover signals with arbitrarily fine resolution. We present simulation results demonstrating graceful degradation of performance with increasing packet loss rate. We also compare the proposed approach with retransmissions. The CS based packet loss mitigation approach was found to maintain up to 99% beat-detection accuracy at packet loss rates of 20%, with a constant latency of less than 2.5 seconds.

Rate adaptation for video telephony in 3G networks

In this paper, we address challenges to packet switched video telephony (PSVT) in 3G wireless networks such as High Speed Packet Access (HSPA), and propose a technique which can improve PSVT service in 3G wireless networks. In HSPA, temporary decrease in available bandwidth can occur based on the user’s location in the cell and/or system loading conditions. This can result in significant increase in observed packet latency, potentially resulting in dropped packets at the receiver. To overcome this problem we describe a feedback based rate adaptation scheme. The proposed scheme is capable of adapting the video encoder bitrate to the varying channel bandwidth and hence minimize the packet latency. The novelty of our proposed approach is that the algorithm matches encoded source rate to varying channel conditions without making any piecewise constant bitrate (CBR) assumptions on the channel. In the proposed scheme the observed throughput is monitored on the uplink (i.e. from sending mobile to the network) and on the downlink (i.e. network to the receiving mobile). The desired target data rate is determined based on these observed throughput. Based on the source variability and the desired target data rate, the algorithm controls the encoding time and packet size (e.g. bytes) of video frames scheduled for transmission. We present simulation results of the proposed approach, based on approved specifications and common simulation conditions adopted in 3GPP and ITU. We show that the one-way delay can be significantly reduced by providing timely feedback of observed throughput from receiving mobile to the sending mobile. By using such a feedback message once every 200 ms, we show that 95 percentile of the packets were delivered with a one-way delay under 250 ms. We also show that our proposed algorithm is capable of graceful degradation based on available system resources and user’s location in the cell.

Channel Modeling of Miniaturized Battery-Powered Capacitive Human Body Communication Systems

Objective: The purpose of this contribution is to estimate the path loss of capacitive human body communication (HBC) systems under practical conditions. Methods: Most prior work utilizes large grounded instruments to perform path loss measurements, resulting in overly optimistic path loss estimates for wearable HBC devices. In this paper, small battery-powered transmitter and receiver devices are implemented to measure path loss under realistic assumptions. A hybrid electrostatic finite element method simulation model is presented that validates measurements and enables rapid and accurate characterization of future capacitive HBC systems. Results: Measurements from form-factor-accurate prototypes reveal path loss results between 31.7 and 42.2 dB from 20 to 150 MHz. Simulation results matched measurements within 2.5 dB. Comeasurements using large grounded benchtop vector network analyzer (VNA) and large battery-powered spectrum analyzer (SA) underestimate path loss by up to 33.6 and 8.2 dB, respectively. Measurements utilizing a VNA with baluns, or large battery-powered SAs with baluns still underestimate path loss by up to 24.3 and 6.7 dB, respectively. Conclusion: Measurements of path loss in capacitive HBC systems strongly depend on instrumentation configurations. It is thus imperative to simulate or measure path loss in capacitive HBC systems utilizing realistic geometries and grounding configurations. Significance: HBC has a great potential for many emerging wearable devices and applications; accurate path loss estimation will improve system-level design leading to viable products.

Artifacts mitigation in ambulatory ECG telemetry

In remote monitoring applications of vital signs including ECG, it is extremely important to ensure that the diagnostic integrity of the signals is not compromised due to the presence of sensing artifacts and channel errors. It is also important for the platform to be extremely power efficient in order to facilitate wearable sensors with user friendly form factors. We present a novel, low power application layer solution that is agnostic to wireless protocols and mitigates artifacts due to packet losses in Body Area Networks (BANs). In our previous work, we presented initial results based on this approach and demonstrated that greater than 99% beat detection accuracy can be achieved even at a packet loss rate as high as 20%. Our contributions in this work include validation of the above on a platform with an ultra low power wearable single lead ECG pendant. We present details of implementation and then extend the platform to mitigate ECG sensing artifacts including power line interference and baseline wandering. The proposed approach enables us to offload most of the complex processing from sensor nodes to the receiver node with better a battery budget, for improved sensor life. Finally, present a qualitative and quantitative assessment of the system.

Digital pacer detection in diagnostic grade ECG

Pulses from a cardiac pacemaker appear as extremely narrow and low- amplitude spikes in an ECG. These get misinterpreted for R-peaks by QRS detectors, leading to subsequent faulty analysis of several algorithms which rely on beat-segmentation. Detection of the pacer pulses, thus, necessitates sampling the ECG signal at high data rates of 4–16 kHz. In a wireless body sensor network, transmission of this high-bandwidth data to a processing gateway, for pacer detection, is extremely power consuming. In this paper, we describe a compressed sensing approach, which enables reliable detection of AAMI/EC11 specified pacer pulses using ECG data rates of 50–100 sps, an order of magnitude smaller than those used in typical detection algorithms in the literature.

Temporal masking for bit-rate reduction in audio codec based on Frequency Domain Linear Prediction

Audio coding based on frequency domain linear prediction (FDLP) uses auto-regressive model to approximate Hilbert envelopes in frequency sub-bands for relatively long temporal segments. Although the basic technique achieves good quality of the reconstructed signal, there is a need for improving the coding efficiency. In this paper, we present a novel method for the application of temporal masking to reduce the bit-rate in a FDLP based codec. Temporal masking refers to the hearing phenomenon, where the exposure to a sound reduces response to following sounds for a certain period of time (up to 200 ms). In the proposed version of the codec, a first order forward masking model of the human ear is implemented and informal listening experiments using additive white noise are performed to obtain the exact noise masking thresholds. Subsequently, this masking model is employed in encoding the sub- band FDLP carrier signal. Application of the temporal masking in the FDLP codec results in a bit-rate reduction of about 10% without degrading the quality. Performance evaluation is done with perceptual evaluation of audio quality (PEAQ) scores and with subjective listening tests.