Bio-integrated wearable systems can measure a broad range of biophysical, biochemical, and environmental signals to provide critical insights into overall health status and to quantify human performance. Recent advances in material science, chemical analysis techniques, device designs, and assembly methods form the foundations for a uniquely differentiated type of wearable technology, characterized by noninvasive, intimate integration with the soft, curved, time-dynamic surfaces of the body. This review summarizes the latest advances in this emerging field of “bio-integrated” technologies in a comprehensive manner that connects fundamental developments in chemistry, material science, and engineering with sensing technologies that have the potential for widespread deployment and societal benefit in human health care. An introduction to the chemistries and materials for the active components of these systems contextualizes essential design considerations for sensors and associated platforms that appear in f...

Bio-Integrated Wearable Systems: A Comprehensive Review

This paper describes the design of a low power, energy-efficient CMOS smart temperature sensor intended for RFID temperature sensing. The BJT-based sensor employs an energy- efficient 2nd-order zoom ADC, which combines a coarse 5-bit SAR conversion with a fine 10-bit ΔΣ conversion. Moreover, a new integration scheme is proposed that halves the conversion time, while requiring no extra supply current. To meet the stringent cost constraints on RFID tags, a fast voltage calibration technique is used, which can be carried out in only 200 msec. After batch calibration and an individual room-temperature calibration, the sensor achieves an inaccuracy of ±0.15°C (3σ) from -55°C to 125°C . Over the same range, devices from a second lot achieved an inaccuracy of ±0.25°C (3σ) in both ceramic and plastic packages. The sensor occupies 0.08 mm2 in a 0.16 μm CMOS process, draws 3.4 μA from a 1.5 V to 2 V supply, and achieves a resolution of 20 mK in a conversion time of 5.3 msec. This corresponds to a minimum energy dissipation of 27 nJ per conversion.

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A CMOS Temperature Sensor With a Voltage-Calibrated Inaccuracy of $\pm$ 0.15 $ ^{\circ}$ C (3 $\sigma$ ) From $-$ 55 $^{\circ}$ C to 125 $^{\circ}$ C

We propose a fully-integrated temperature sensor for battery-operated, ultra-low power microsystems. Sensor operation is based on temperature independent/dependent current sources that are used with oscillators and counters to generate a digital temperature code. A conventional approach to generate these currents is to drop a temperature sensitive voltage across a resistor. Since a large resistance is required to achieve nWs of power consumption with typical voltage levels (100 s of mV to 1 V), we introduce a new sensing element that outputs only 75 mV to save both power and area. The sensor is implemented in 0.18 μm CMOS and occupies 0.09 mm 2
 while consuming 71 nW. After 2-point calibration, an inaccuracy of + 1.5°C/-1.4°C is achieved across 0 °C to 100 °C. With a conversion time of 30 ms, 0.3 °C (rms) resolution is achieved. The sensor does not require any external references and consumes 2.2 nJ per conversion. The sensor is integrated into a wireless sensor node to demonstrate its operation at a system level.

A Fully-Integrated 71 nW CMOS Temperature Sensor for Low Power Wireless Sensor Nodes

A four-levels hierarchical wireless body sensor network (WBSN) system is designed for biometrics and healthcare applications. It also separates pathways for communication and control. In order to improve performance, a communication cycle is constructed for synchronizing the WBSN system with the pipeline. A low-power adaptive process is a necessity for long-time healthcare monitoring. It includes a data encoder and an adaptive power conserving algorithm within each sensor node along with an accurate control switch system for adaptive power control. The thermal sensor node consists of a micro control unit (MCU), a thermal bipolar junction transistor sensor, an analog-to-digital converter (ADC), a calibrator, a data encoder, a 2.4-GHz radio frequency transceiver, and an antenna. When detecting ten body temperature or 240 electrocardiogram (ECG) signals per second, the power consumption is either 106.3 ?W or 220.4 ?W. By switching circuits, multi sharing wireless protocol, and reducing transmission data by data encoder, it achieves a reduction of 99.573% or 99.164% in power consumption compared to those without using adaptive and encoding modules. Compared with published research reports and industrial works, the proposed method is 69.6% or 98% lower than the power consumption in thermal sensor nodes which consist only of a sensor and ADC (without MCU, 2.4-GHz transceiver, modulator, demodulator, and data encoder) or wireless ECG sensor nodes which selected Bluetooth, 2.4-GHz transceiver, and Zigbee as wireless protocols.

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Wireless Body Sensor Network With Adaptive Low-Power Design for Biometrics and Healthcare Applications

A CMOS bandgap reference with an inaccuracy of ±0.15% (3 σ) from -40°C to 125°C is presented. In contrast to prior art, it requires only a single trim to achieve this level of precision. A detailed analysis of the various error sources is provided, and techniques to reduce them are discussed. The prototype bandgap reference draws 55 μA from a 1.8 V supply, and occupies 0.12 mm2 in a 0.16 μm CMOS process. Experimental results from two runs show that, with the use of chopping and higher-order curvature correction to remove non-PTAT errors, the residual error of a bandgap reference is mainly PTAT, and can be removed by a single room temperature trim.

A Single-Trim CMOS Bandgap Reference With a $3\sigma$ Inaccuracy of $\pm$ 0.15% From ${-}$ 40 $^{\circ}$ C to 125 $^{\circ}$ C

A low-cost temperature sensor with on-chip sigma-delta ADC and digital bus interface was realized in a 0.5 /spl mu/m CMOS process. Substrate PNP transistors are used for temperature sensing and for generating the ADC's reference voltage. To obtain a high initial accuracy in the readout circuitry, chopper amplifiers and dynamic element matching are used. High linearity is obtained by using second-order curvature correction. With these measures, the sensor's temperature error is dominated by spread on the base-emitter voltage of the PNP transistors. This is trimmed after packaging by comparing the sensor's output with the die temperature measured using an extra on-chip calibration transistor. Compared to traditional calibration techniques, this procedure is much faster and therefore reduces production costs. The sensor is accurate to within /spl plusmn/0.5/spl deg/C (3/spl sigma/) from -50/spl deg/C to 120/spl deg/C.

/pdf/a-cmos-smart-temperature-sensor-with-a-3-spl-sigma-2p2eio6n5v.pdf

A. Bakker

Papers

A CMOS smart temperature sensor with a 3/spl sigma/ inaccuracy of /spl plusmn/0.1/spl deg/C from -55/spl deg/C to 125/spl deg/C