Ultra-Thin Chip Package (UTCP) and stretchable circuit technologies for wearable ECG system

A comfortable, wearable wireless ECG monitoring system is proposed. The device is realized using the combination of two proprietary advanced technologies for electronic packaging and interconnection : the UTCP (Ultra-Thin Chip Package) technology and the SMI (Stretchable Mould Interconnect) technology for elastic and stretchable circuits. Introduction of these technologies results in small fully functional devices, exhibiting a significant increase in user comfort compared to devices fabricated with more conventional packaging and interconnection technologies

Low power wireless sensor network for structural health monitoring of buildings using MEMS strain sensors and accelerometers

Within the MEMSCON project, a wireless sensor network was developed for structural health monitoring of buildings to assess earthquake damage. The sensor modules use custom-developed capacitive MEMS strain and 3D acceleration sensors and a low power readout application-specific integrated circuit (ASIC). A low power network architecture was implemented on top of an 802.15.4 media access control (MAC) layer in the 900MHz band. A custom patch antenna was designed in this frequency for optimal integration into the sensor modules. The strain sensor modules measure periodically or on-demand from the base station and obtain a battery lifetime of 12 years. The accelerometer modules record during an earthquake event, which is detected using a combination of the local acceleration data and remote triggering from the base station, based on the acceleration data from multiple sensors across the building. They obtain a battery lifetime of 2 years. The MEMS strain sensor and its readout ASIC were packaged in a custom package suitable for mounting onto a reinforcing bar inside the concrete and without constraining the moving parts of the MEMS strain sensor. The wireless modules, including battery and antenna, were packaged in a robust housing compatible with mounting in a building and accessible for maintenance such as battery replacement

3D Integration of ultra-thin functional devices inside standard multilayer flex laminates

Nowadays, more and more wearable electronic systems are being realized on flexible substrates. Main limiting factor for the mechanical flexibility of those wearable systems are typically the rigid components - especially the relatively large active components - mounted on top and bottom of the flex substrates. Integration of these active devices inside the flex multilayers will not only enable for a high degree of miniaturization but can also improve the total flexibility of the system. This paper now presents a technology for the 3D embedding of ultra-thin active components inside standard flex laminates. Active components are first thinned down to 20-25 mu m, and packaged as an Ultra-Thin Chip Pack-age (UTCP). These UTCP packages will serve as flexible interposer: all layers are so thin, that the whole package is even bendable. The limited total pack-age thickness of only 60 mu m makes them also suitable for lamination in between commercial flex panels, replacing for example the direct die integration. A fan-out metallization on the package facilitates easy testing before integration, solving the KGD issue, and can also relax the chip contact pitch, excluding the need for very precise placement and the use of expensive, fine-pitch flex substrates. The technology is successfully demonstrated for the 3D-integration of a Texas Instrument MSP430 low-power microcontroller, inside the conventional double sided flex laminate of a wireless ECG system. The microcontrollers are first thinned down and UTCP pack-aged These pack-ages are then laminated in between the large panels of the flex multilayer stack and finally connected to the different layers of the flex board by metallized through-hole interconnects. The thinning down, the UTCP pack-aging and the 3D-integration inside the commercial flex panels did not have any affect on the functionality of the TI microcontroller. Smaller SMD's were finally mounted on top and bottom of the integrated device

Low power wireless sensor network for building monitoring

A wireless sensor network is proposed for monitoring buildings to assess earthquake damage. The sensor nodes use custom-developed capacitive MEMS strain and 3D acceleration sensors and a low power readout ASIC for a battery life of up to 12 years. The strain sensors are mounted at the base of the building to measure the settlement and plastic hinge activation of the building after an earthquake. They measure periodically or on-demand from the base station. The accelerometers are mounted at every floor of the building to measure the seismic response of the building during an earthquake. They record during an earthquake event using a combination of the local acceleration data and remote triggering from the base station based on the acceleration data from multiple sensors across the building. A low power network architecture was implemented over an 802.15.4 MAC in the 900MHz band. A custom patch antenna was designed in this frequency band to obtain robust links in real-world conditions

In vivo validation of the electronic depth control probes.

In this article, we evaluated the electrophysiological performance of a novel, high-complexity silicon probe array. This brain-implantable probe implements a dynamically reconfigurable voltage-recording device, coordinating large numbers of electronically switchable recording sites, referred to as electronic depth control (EDC). Our results show the potential of the EDC devices to record good-quality local field potentials, and single- and multiple-unit activities in cortical regions during pharmacologically induced cortical slow wave activity in an animal model

Capacitively-Coupled ECG and Respiration for Sleep-Wake Prediction and Risk Detection in Sleep Apnea Patients

Obstructive sleep apnea (OSA) patients would strongly benefit from comfortable home diagnosis, during which detection of wakefulness is essential. Therefore, capacitively-coupled electrocardiogram (ccECG) and bioimpedance (ccBioZ) sensors were used to record the sleep of suspected OSA patients, in parallel with polysomnography (PSG). The three objectives were quality assessment of the unobtrusive signals during sleep, prediction of sleep–wake using ccECG and ccBioZ, and detection of high-risk OSA patients. First, signal quality indicators (SQIs) determined the data coverage of ccECG and ccBioZ. Then, a multimodal convolutional neural network (CNN) for sleep–wake prediction was tested on these preprocessed ccECG and ccBioZ data. Finally, two indices derived from this prediction detected patients at risk. The data included 187 PSG recordings of suspected OSA patients, 36 (dataset “Test”) of which were recorded simultaneously with PSG, ccECG, and ccBioZ. As a result, two improvements were made compared to prior studies. First, the ccBioZ signal coverage increased significantly due to adaptation of the acquisition system. Secondly, the utility of the sleep–wake classifier increased as it became a unimodal network only requiring respiratory input. This was achieved by using data augmentation during training. Sleep–wake prediction on “Test” using PSG respiration resulted in a Cohen’s kappa ([Formula: see text]) of 0.39 and using ccBioZ in [Formula: see text] = 0.23. The OSA risk model identified severe OSA patients with a [Formula: see text] of 0.61 for PSG respiration and [Formula: see text] of 0.39 using ccBioZ (accuracy of 80.6% and 69.4%, respectively). This study is one of the first to perform sleep–wake staging on capacitively-coupled respiratory signals in suspected OSA patients and to detect high risk OSA patients based on ccBioZ. The technology and the proposed framework could be applied in multi-night follow-up of OSA patients

Automatic radar-based 2-D localization exploiting vital signs signatures

In light of the continuously and rapidly growing senior and geriatric population, the research of new technologies enabling long-term remote patient monitoring plays an important role. For this purpose, we propose a single-input-multiple-output (SIMO) frequency-modulated continuous wave (FMCW) radar system and a signal processing technique to automatically detect the number and the 2-D position (azimuth and range information) of stationary people (seated/lying down). This is achieved by extracting the vital signs signatures of each single individual, separating the Doppler shifts caused by the cardiopulmonary activities from the unwanted reflected signals from static reflectors and multipaths. We then determine the number of human subjects present in the monitored environment by counting the number of extracted vital signs signatures while the 2-D localization is performed by measuring the distance from the radar where the vital signs information is sensed (i.e., locating the thoracic region). We reported maximum mean absolute errors (MAEs) of 0.1 m and 2.29[Formula: see text] and maximum root-mean-square errors (RMSEs) of 0.12 m and 3.04[Formula: see text] in measuring respectively the ranges and azimuth angles. The experimental validation demonstrated the ability of the proposed approach in monitoring paired human subjects in a typical office environment