No abstract

As the population ages and the risk of chronic disease increases, the cost of healthcare will rise. Technology for mobile telemetry could reduce cost and improve the efficiency of treatment. In order to achieve these goals, we first need to overcome several technical challenges, including sufficient system lifetime, high signal fidelity, and adequate security. In this paper we present the design, implementation, and evaluation of a Mobile Biotelemetric System (MBS) that addresses these remote medical monitoring challenges. MBS comprises a custom low-power sensor node that accurately collects and analyzes electrocardiogram (ECG) data, a client service with a multifaceted policy engine that evaluates the data, and a web portal interface for visualizing ECG data streams. MBS differs from other remote monitoring systems primarily in the policy engine's ability to provide flexible, robust, and precise system communication from end-to-end and to enable tradeoffs in metrics such as power and transmission frequency. We show that, given a representative set of ECG signals, policies can be set to make the operation of the hardware and software resilient against transient ECG conditions. Further, we incorporate state-of-the-art security practices to safeguard our data and foil common attacks.

This paper examines the requirements of wearable sensing applications and their implications for designing the next generation of body area sensors. We define key metrics for wearable sensors and discuss how body area sensors differ from generic wireless sensors. To explore the system level issues with a wearable node, we show measurements from a wearable electrocardiogram (ECG) sensor prototype. Using heart rate monitoring as an example, we show how ultra low power (ULP) circuit design must be applied to support the stringent energy and/or power demands of longlife wearable sensors. Specifically, sub-threshold operation of digital circuits creates opportunities for re-thinking the entire system. We conclude that we can only reach the lower limits of power consumption through cross-hierarchy design of the entire sensor node that leverages ULP digital circuits.

An Automated Unique Tagging System (AUTS) is presented, intended for RFID applications, that generates identification numbers based on random process variations, circumventing the need for non-volatile memories such as EEPROM or Flash. A sense amplifier is used to measure the mismatch in threshold voltage between two identical NMOS devices and generate a 1-bit random output. The AUTS has been fabricated in the TSMC 0.25µm CMOS process and tested.

A 39 fJ/bit IC identification system based on FET mismatch is presented and implemented in a 130 nm CMOS process. ID bits are generated based on the ∆V T between identically drawn NMOS devices due to manufacturing variation, and the ID cell structure allows for the characterization of ID bit reliability by characterizing ∆V T. An addressing scheme is also presented that allows for reliable on-chip identification of ICs in the presence of unreliable ID bits. An example implementation is presented that can address 1000 unique ICs, composed of 31 ID bits and having an error rate less than 10 −6 , with up to 21 unreliable bits.