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This work presents a power-efficient level crossing (LC) ADC designed to digitize sparse signals. It uses dynamically self-biased comparators, which require minimal current when the input voltage is far from a decision threshold. It also uses a DAC architecture which avoids the signal attenuation commonly present in prior LC ADC works, improving the achievable SNDR. The prototype is designed and implemented in a 65-nm CMOS technology, and occupies an area of 0.0045 mm2. In a 20 kHz bandwidth, the LC-ADC achieves a 64 dB SNDR. Thanks to the proposed techniques a power efficiency of up to 1.8 fJ/conv.-step is achieved for sinusoidal inputs. For sparse biopotential signals, a FoMW as low as 0.9 fJ/conv.-step was measured. This makes the prototype interesting for e.g., biomedical applications that make use of spike-based processing.

Objective: Sensing with capacitive electrodes is of interest for long-term, comfortable bio-potential measurements (e.g., ECG). However, due to the small body-to-electrode capacitance (C e ), the design of the associated front-end amplifier remains a challenge. Both voltage amplifiers (VA) and charge amplifiers (CA) can be employed. While basic comparisons of both typologies were done before, this paper extends the comparison to their responses to artifacts (caused by motion or interference). Further, a VA-CA-switchable amplifier is proposed, allowing to adapt the amplifier type to different situations, and enabling to estimate the body-to-electrode capacitance C e in a passive way. Methods: A VA-CA switchable amplifier was implemented in a 180 nm CMOS process. The responses to artifacts for VA and CA were studied by modelling, simulations and experiments using the custom IC. The proposed C e estimation method was validated by electrical tests and in-vivo tests. Results: VAs are less affected by C e variation artifacts, while CAs recover faster from triboelectricity artifacts. In a VA, these two artifacts are multiplicative and get modulated if they occur simultaneously, but in a CA they remain independent. Conclusion: The combined VA-CA amplifier has the potential for optimal amplifier selection according to the properties of the recorded signal, the value of C e and the actual presence of artifacts. Moreover, it can estimate C e without extra hardware. Significance: The proposed VA-CA switchable structure is superior to an individual VA or CA, thanks its adaptability to signal quality and artifacts, and it provides extra information on the body-to-electrode interface quality (C e ).

With the advent of small, battery-powered devices, power efficiency has become of paramount importance. For analog-to-digital converters (ADCs), the successive approximation register (SAR) architecture plays a prominent role thanks to its ability to combine power efficiency with a simple architecture, a broad application scope, and technology portability. In this review article, the basic design challenges for low-power SAR ADCs are summarized and several design techniques are illustrated. Furthermore, the limitations of SAR ADCs are outlined and hybrid architecture trends, such as noise-shaping SAR ADCs and pipelined SAR ADCs, are briefly introduced and clarified with examples.

Example embodiments relate to systems and methods for analog-to-digital signal conversion. One embodiment includes a system for analog-to-digital signal conversion. The system includes an analog input signal. The system also includes a digital-to-analog converter configured to generate a reference signal. Further, the system includes an amplifier configured to amplify an error signal that includes a difference between the analog input signal and the reference signal. Additionally, the system includes a level-crossing based sampling circuit that includes a first comparator configured to compare the error signal with respect to a first reference level, and a second comparator configured to compare the error signal with respect to a second reference level, thereby generating event-based reset signals corresponding to a plurality of sampling instances in order to reset the digital-to-analog converter. Yet further, the system includes a trigger circuit configured to generate reset signals asynchronous to the event-based reset signals.

This paper presents an ultrasound rangefinder system able to find relative distances among energy-constrained sensor nodes. The nodes build a swarm that is operated in collision and multipath rich environments. A new distance measurement technique combining Wake-up and Frequency Modulated Continuous Wave (FMCW) is proposed to enable the ranging while neglecting the echoes from passive reflectors in the environment. The building blocks of the sensor nodes comprise a transmitter, a wake-up receiver, and a ranging receiver, all implemented in a 65 nm CMOS technology. The transmitter includes two switched-capacitor converters and an output multiplexer to generate a four-level driving signal and broadcast either a wake-up sequence or a digitally synthesized ultrasound Chirp. The transmitter dissipates 0.43μ J and 0.82μ J to broadcast the wake-up signal and the Chirp, respectively. A mixer first architecture is exploited in the wake-up receiver to reduce the always-on power consumption of the nodes. The ranging receiver uses a heterodyne architecture suited for the FMCW. The power consumption of the wake-up receiver and ranging receiver is 23.6 nW and 0.56μ W, respectively. The proposed rangefinder is experimentally characterized up to a 1 m distance in air and dissipates 1.25μ J per measurement, achieving a resolution of 18.7 mm at 0.55 m.

Multi-channel measurements from the maternal abdomen acquired by means of dry electrodes can be employed to promote long-term monitoring of fetal heart rate (fHR). The signals acquired with this type of electrode have a lower signal-to-noise ratio and different artifacts compared to signals acquired with conventional wet electrodes. Therefore, starting from the benchmark algorithm with the best performance for fHR estimation proposed by Varanini et al., we propose a new method specifically designed to remove artifacts typical of dry-electrode recordings. To test the algorithm, experimental textile electrodes were employed that produce artifacts typical of dry and capacitive electrodes. The proposed solution is based on a hybrid (hardware and software) pre-processing step designed specifically to remove the disturbing component typical of signals acquired with these electrodes (triboelectricity artifacts and amplitude modulations). The following main processing steps consist of the removal of the maternal ECG by blind source separation, the enhancement of the fetal ECG and identification of the fetal QRS complexes. Main processing is designed to be robust to the high-amplitude motion artifacts that corrupt the acquisition. The obtained denoising system was compared with the benchmark algorithm both on semi-simulated and on real data. The performance, quantified by means of sensitivity, F1-score and root-mean-square error metrics, outperforms the performance obtained with the original method available in the literature. This result proves that the design of a dedicated processing system based on the signal characteristics is necessary for reliable and accurate estimation of the fHR using dry, textile electrodes.

Long-term ambulatory monitoring of the fetal heart rate (fHR) can greatly increase insight into fetal well-being and reduce pregnancy risks. Unfortunately, the existing solutions using wet or dry electrodes are unsuitable for long-term fHR monitoring due to the use of a gel or direct skin contact. Capacitive electrodes can measure an electrocardiographic (ECG) signal through clothes and, therefore, are perfectly suitable for long-term monitoring of the fHR. However, capacitive fetal ECG (fECG) measurements are challenging due to the high sensitivity of capacitive sensors to motion artifacts (MAs) and the low amplitude of the fECG. This article aims at investigating the feasibility of fECG measurements using capacitive electrodes with dedicated postprocessing algorithms for signal-to-noise ratio (SNR) improvement and MA reduction. To this end, a novel simulator of the full measurement chain is realized that generates multichannel capacitive fECG data with artificial MAs and system noise. A dedicated blind source separation (BSS) algorithm is then employed for MA removal and fECG extraction. The extracted fECG is evaluated by SNR calculation and R-peak detection. Our results show that the BSS algorithm may extract the fECG signal from noisy capacitive data. In addition, lower system noise or higher number of channels may lead to better fECG extraction. A maximum increase of 0.5 dB in the SNR and decrease of 80.7 % in the R-peak detection error are observed with increased electrode number from 8 to 20. Our findings provide useful insights for the hardware design of a capacitive fECG measurement system.

We present a 5-sensor, fully integrated sensing system with interchangeable sensors and programmable configuration to create a sub-microWatt multisensor node that can tackle a wide range of sensing applications. Furthermore, the sensor node is capable of autonomously adapting its configuration to the application requirements hence minimizing system power. Such self-reconfiguration is enabled at low overhead by developing an automated offline optimization strategy, in combination with an autonomous embedded configuration controller, using the concept of behavioral trees (BTs). The resulting fully integrated platform consumes a maximum of 321 nW when sampling at 500 Hz and 3025 nW at 8 kHz. Furthermore, we demonstrate the end-to-end autonomous optimization flow for two different applications exploiting different sensors: 1) human activity recognition using accelerometers and 2) machine listening using a microphone. Both use cases demonstrate that the introduced system and methodology reduces the power by more than a factor 2 without losing significant application detection accuracy.

This letter presents the design and experimental characterization of an ultrasound rangefinder system. A new distance measurement method is proposed for determining the relative position among sensor nodes that are operated in a collision and multipath rich environment, while needing no common time reference between them. A 65 nm CMOS technology has been used to build the sensor nodes, which comprise an on-chip receiver and transmitter. The proposed rangefinder system is characterized up to 1 m in air and has a range resolution of 6.5 mm, while dissipating 2.67~\mu {\mathrm{ J}} per measurement.

This paper presents the design and experimental characterization of an ultrasound transceiver. The transceiver includes an on-chip transmitter and a receiver to be used in a symmetric data-link, where each sensor node has limited energy resources and is operated in air or a fluidic environment. The receiver and the transmitter operate from a 0.8V supply and consume 1.18μW and 50μW, respectively, while exchanging data at 1kbps data-rate. The receiver sensitivity is -81.6dBm at a 10-3 Bit Error Rate (BER) level, which enables an experimentally verified transmission over 3.2m in air and a predicted transmission distance in water in the order of 2km, with a measured energy per bit performance of 51.18 nJ/b.

Electrocardiography (ECG) measurements are essential components in clinical diagnosis and monitoring. Conventional ECG measurements produce discomfort to the patients due to the use of gel and direct skin contact. Capacitive electrodes can measure ECG signals through an isolation layer; they are especially suitable for long-term ambulatory monitoring. However, capacitive ECG measurements are severely affected by motion artifacts (MAs) due to variable coupling distance. Adaptive filtering has been widely used for MA reduction in ECG measurements. Unfortunately, a reference signal recorded by additional sensors is required for the existing adaptive-filtering methods, limiting their applicability in ambulatory settings. In this paper on capacitive ECG recordings, a novel adaptive-filtering method is proposed for MA removal, where the reference signal is extracted from the power-line interference (PLI). PLI is particularly evident in a capacitive ECG due to unbalanced coupling capacitance. Along with MAs, electrode movement causes variations in the PLI amplitude. By demodulating the PLI, a reference signal reflecting variations in the coupling capacitance can be extracted for adaptive MA removal. The proposed method was evaluated both by simulations and real data and compared with the acceleration-based adaptive-filtering method. Comparable or higher ECG signal-to-noise ratio was achieved by the proposed method with a computational cost of 79 μs/iteration, indicating effective MA removal. The proposed method may, therefore, lead to improved analysis of capacitive ECG signals in ambulatory settings.