An unsupervised behavioral modeling and alerting system based on passive sensing for elderly care

Artificial Intelligence in combination with the Internet of Medical Things enables remote healthcare services through networks of environmental and/or personal sensors. We present a remote healthcare service system which collects real-life data through an environmental sensor package, including binary motion, contact, pressure, and proximity sensors, installed at households of elderly people. Its aim is to keep the caregivers informed of subjects’ health-status progressive trajectory, and alert them of health-related anomalies to enable objective on-demand healthcare service delivery at scale. The system was deployed in 19 households inhabited by an elderly person with post-stroke condition in the Emilia–Romagna region in Italy, with maximal and median observation durations of 98 and 55 weeks. Among these households, 17 were multi-occupancy residences, while the other 2 housed elderly patients living alone. Subjects’ daily behavioral diaries were extracted and registered from raw sensor signals, using rule-based data pre-processing and unsupervised algorithms. Personal behavioral habits were identified and compared to typical patterns reported in behavioral science, as a quality-of-life indicator. We consider the activity patterns extracted across all users as a dictionary, and represent each patient’s behavior as a ‘Bag of Words’, based on which patients can be categorized into sub-groups for precision cohort treatment. Longitudinal trends of the behavioral progressive trajectory and sudden abnormalities of a patient were detected and reported to care providers. Due to the sparse sensor setting and the multi-occupancy living condition, the sleep profile was used as the main indicator in our system. Experimental results demonstrate the ability to report on subjects’ daily activity pattern in terms of sleep, outing, visiting, and health-status trajectories, as well as predicting/detecting 75% hospitalization sessions up to 11 days in advance. 65% of the alerts were confirmed to be semantically meaningful by the users. Furthermore, reduced social interaction (outing and visiting), and lower sleep quality could be observed during the COVID-19 lockdown period across the cohort

Validation of the porous-medium approach to model interlayer-cooled 3D-chip stacks

Interlayer cooling is the only heat removal concept which scales with the number of active tiers in a vertically integrated chip stack. In this work, we numerically and experimentally characterize the performance of a three tier chip stack with a footprint of 1cm2. The implementation of 100μm pitch area array interconnect compatible heat transfer structures results in a maximal junction temperature increase of 54.7K at 1bar pressure drop with water as coolant for 250W/cm2 hot-spot and 50W/cm2 background heat flux. The total power removed was 390W which corresponds to a 3.9kW/cm3 volumetric heat flow. An efficient multi-scale modeling approach is proposed to predict the temperature response in the complete chip stack. The experimental validation confirmed an accuracy of +/- 10%. Detailed sub-domain modeling with parameter extraction is the base for the system level porous-media calculations with thermal field-coupling between solid – fluid and solid – solid interfaces. Furthermore, the strength and weakness of microchannel and pin fin heat transfer geometries in 2-port and 4-port fluid architectures is identified. Microchannels efficiently mitigate hot spots by distributing the dissipated heat to multiple cavities due to their low porosity. Pin fins with improved permeability and convective heat dissipation are advantageous at small power map contrast and aligned hot spots on the different tiers. Large stacks of 4cm2 can be cooled sufficiently by the 4-port fluid delivery architecture. The flow rate is improved four times compared to the 2-port fluid manifold. The non-uniformity of the flow in case of the 4-port demands a more careful floor- planning with hot spots placed in the chip stack corners. This is especially true in case of communicating heat transfer geometries such as pin fin structures with zero fluid velocity in the stack center. This large velocity contrast can be reduced by the implementation of non- communicating microchannels

HIGH PERFORMANCE THERMAL INTERFACE TECHNOLOGY OVERVIEW

An overview on recent developments in thermal interfaces is given with a focus on a novel thermal interface technology that allows the formation of 2-3 times thinner bondlines with strongly improved thermal properties at lower assembly pressures. This is achieved using nested hierarchical surface channels to control the particle stacking with highly particle-filled materials. Reliability testing with thermal cycling has also demonstrated a decrease in thermal resistance after extended times with longer overall lifetime compared to a flat interface

Extended tensor description to design non-uniform heat-removal in interlayer cooled chip stacks

Interlayer cooling is a heat removal concept that scales with the number of stacked tiers. Uniform fluid cavities result only in moderate heat removal performance. A substantial improvement could be expected for nonuniform, hot-spot-aware fluid cavities. Hence, we propose an extension of our multi-scale modeling framework to support nonuniform fluid cavity designs. The chip stack with its cavities and the silicon dies are represented by field-coupled porous and solid domains, respectively. Detailed sub-domain modeling using two pairs of periodic boundary conditions for fully and half populated pin-fin arrays with 100 m height and pitch was performed. Permeability and convective thermal resistance values with respect to arbitrary flow directions were extracted. These values are used in the chip stack model to predict the mass and the energy transport within the fluid cavity and between the domains, respectively. Three mathematical permeability descriptions are benchmarke d against each other and are experimentaly validated. The extended tensor description predicts the mass flow and maximum junction temperature best at an accuracy of better than 20%. We could also demonstrate the extension of interlayer cooling to TSV pitches of 50 m with hot-spot heat fluxes of up to 250W/cm 2 by pin-fin-density modulation and four-port fluid delivery

Thermo-mechanical reliability of sintered all-Cu electrical fine pitch interconnects under isothermal fatigue testing benchmarked against soldered and TLP-bonded SnAg3.5 joints

Cu sintering is one of the emerging technologies in the field of micro- and power electronics where operating temperatures higher than 150°C are required. At these temperatures, solder joints reach their limits due to high homologous temperatures. Hence, Cu sintered joints can serve as a substitute for these soft solder joints, being advantageous also with respect to thermo-dynamic stability, fatigue resistance, electrical conductance and cost. This paper addresses failure analysis of sintered (neck-based) All-Cu electrical interconnects (NEI) along with soldered SnAg3.5 and transient liquid phase bonded (TLPB) specimens which form an SnCu intermetallic (IMC) and are used in a homogenous Si-Si flip chip assembly for fine pitch interconnects. The SnAg3.5 solder serves as a benchmark for the NEIs and the TLPB joints. All the flip chip specimens were free of underfill material. The test samples were assembled on spring steel substrates using a Silicone-based adhesive for a low stress bond and then put under isothermal accelerated fatigue tests using 4-point bending at low-homologous temperatures (R.T.). The reliability investigation involves monitoring of electrical resistance as a failure indicator for interconnect fatigue. A failure criterion at 20% increase in resistance is defined to establish a correlation between the experimental failure times and resistance. The fatigue behaviour of the joints was also studied using Finite Elements analysis (FEA). The focus of the modelling was towards the behaviour of the critical joint. Cross-sections were prepared and analysed using optical microscopy and SEM to investigate the failure mode and mechanism