Prediction of state anxiety by machine learning applied to photoplethysmography data.

BACKGROUND: As the human behavior is influenced by both cognition and emotion, affective computing plays a central role in human-machine interaction. Algorithms for emotions recognition are usually based on behavioral analysis or on physiological measurements (e.g., heart rate, blood pressure). Among these physiological signals, pulse wave propagation in the circulatory tree can be assessed through photoplethysmography (PPG), a non-invasive optical technique. Since pulse wave characteristics are influenced by the cardiovascular status, which is affected by the autonomic nervous activity and hence by the psychophysiological state, PPG might encode information about emotional conditions. The capability of a multivariate data-driven approach to estimate state anxiety (SA) of healthy participants from PPG features acquired on the brachial and radial artery was investigated. METHODS: The machine learning method was based on General Linear Model and supervised learning. PPG was measured employing a custom-made system and SA of the participants was assessed through the State-Trait Anxiety Inventory (STAI-Y) test. RESULTS: A leave-one-out cross-validation framework showed a good correlation between STAI-Y score and the SA predicted by the machine learning algorithm (r = 0.81; p = 1.87∙10-9). The preliminary results suggested that PPG can be a promising tool for emotions recognition, convenient for human-machine interaction applications.

Fiberless, Multi-Channel fNIRS-EEG System Based on Silicon Photomultipliers: Towards Sensitive and Ecological Mapping of Brain Activity and Neurovascular Coupling.

Portable neuroimaging technologies can be employed for long-term monitoring of neurophysiological and neuropathological states. Functional Near-Infrared Spectroscopy (fNIRS) and Electroencephalography (EEG) are highly suited for such a purpose. Their multimodal integration allows the evaluation of hemodynamic and electrical brain activity together with neurovascular coupling. An innovative fNIRS-EEG system is here presented. The system integrated a novel continuous-wave fNIRS component and a modified commercial EEG device. fNIRS probing relied on fiberless technology based on light emitting diodes and silicon photomultipliers (SiPMs). SiPMs are sensitive semiconductor detectors, whose large detection area maximizes photon harvesting from the scalp and overcomes limitations of fiberless technology. To optimize the signal-to-noise ratio and avoid fNIRS-EEG interference, a digital lock-in was implemented for fNIRS signal acquisition. A benchtop characterization of the fNIRS component showed its high performances with a noise equivalent power below 1 pW. Moreover, the fNIRS-EEG device was tested in vivo during tasks stimulating visual, motor and pre-frontal cortices. Finally, the capabilities to perform ecological recordings were assessed in clinical settings on one Alzheimer's Disease patient during long-lasting cognitive tests. The system can pave the way to portable technologies for accurate evaluation of multimodal brain activity, allowing their extensive employment in ecological environments and clinical practice.

Multi-Site Photoplethysmographic and Electrocardiographic System for Arterial Stiffness and Cardiovascular Status Assessment.

The development and validation of a system for multi-site photoplethysmography (PPG) and electrocardiography (ECG) is presented. The system could acquire signals from 8 PPG probes and 10 ECG leads. Each PPG probe was constituted of a light-emitting diode (LED) source at a wavelength of 940 nm and a silicon photomultiplier (SiPM) detector, located in a back-reflection recording configuration. In order to ensure proper optode-to-skin coupling, the probe was equipped with insufflating cuffs. The high number of PPG probes allowed us to simultaneously acquire signals from multiple body locations. The ECG provided a reference for single-pulse PPG evaluation and averaging, allowing the extraction of indices of cardiovascular status with a high signal-to-noise ratio. Firstly, the system was characterized on optical phantoms. Furthermore, in vivo validation was performed by estimating the brachial-ankle pulse wave velocity (baPWV), a metric associated with cardiovascular status. The validation was performed on healthy volunteers to assess the baPWV intra- and extra-operator repeatability and its association with age. Finally, the baPWV, evaluated via the developed instrumentation, was compared to that estimated with a commercial system used in clinical practice (Enverdis Vascular Explorer). The validation demonstrated the system's reliability and its effectiveness in assessing the cardiovascular status in arterial ageing.

Stretchable wireless system for sweat pH monitoring.

Sensor-laden wearable systems that are capable of providing continuous measurement of key physiological parameters coupled with data storage, drug delivery and feedback therapy have attracted huge interest. Here we report a stretchable wireless system for sweat pH monitoring, which is able to withstand up to 53% uniaxial strain and more than 500 cycles to 30% strain. The stretchability of the pH sensor patch is provided by a pair of serpentine-shaped stretchable interconnects. The pH sensing electrode is made of graphite-polyurethane composite, which is suitable for biosensor application. The sensing patch validated through in-depth electrochemical studies, exhibits a pH sensitivity of 11.13 ±â€¯5.8 mV/pH with a maximum response time of 8 s. Interference study of ions and analyte (Na+, K+ and glucose) in test solutions shows negligible influence on the pH sensor performance. The pH data can be wirelessly and continuously transmitted to smartphone through a stretchable radio-frequency-identification antenna, of which the radiating performance is stable under 20% strain, as proved by vector network analyzer measurement. To evaluate the full system, the pH value of a human sweat equivalent solution has been measured and wirelessly transmitted to a custom-developed smart phone App.

Nanowire FET Based Neural Element for Robotic Tactile Sensing Skin.

This paper presents novel Neural Nanowire Field Effect Transistors (υ-NWFETs) based hardware-implementable neural network (HNN) approach for tactile data processing in electronic skin (e-skin). The viability of Si nanowires (NWs) as the active material for υ-NWFETs in HNN is explored through modeling and demonstrated by fabricating the first device. Using υ-NWFETs to realize HNNs is an interesting approach as by printing NWs on large area flexible substrates it will be possible to develop a bendable tactile skin with distributed neural elements (for local data processing, as in biological skin) in the backplane. The modeling and simulation of υ-NWFET based devices show that the overlapping areas between individual gates and the floating gate determines the initial synaptic weights of the neural network - thus validating the working of υ-NWFETs as the building block for HNN. The simulation has been further extended to υ-NWFET based circuits and neuronal computation system and this has been validated by interfacing it with a transparent tactile skin prototype (comprising of 6 × 6 ITO based capacitive tactile sensors array) integrated on the palm of a 3D printed robotic hand. In this regard, a tactile data coding system is presented to detect touch gesture and the direction of touch. Following these simulation studies, a four-gated υ-NWFET is fabricated with Pt/Ti metal stack for gates, source and drain, Ni floating gate, and Al2O3 high-k dielectric layer. The current-voltage characteristics of fabricated υ-NWFET devices confirm the dependence of turn-off voltages on the (synaptic) weight of each gate. The presented υ-NWFET approach is promising for a neuro-robotic tactile sensory system with distributed computing as well as numerous futuristic applications such as prosthetics, and electroceuticals.

Advances in the fabrication of graphene transistors on flexible substrates.

Graphene is an ideal candidate for next generation applications as a transparent electrode for electronics on plastic due to its flexibility and the conservation of electrical properties upon deformation. More importantly, its field-effect tunable carrier density, high mobility and saturation velocity make it an appealing choice as a channel material for field-effect transistors (FETs) for several potential applications. As an example, properly designed and scaled graphene FETs (Gr-FETs) can be used for flexible high frequency (RF) electronics or for high sensitivity chemical sensors. Miniaturized and flexible Gr-FET sensors would be highly advantageous for current sensors technology for in vivo and in situ applications. In this paper, we report a wafer-scale processing strategy to fabricate arrays of back-gated Gr-FETs on poly(ethylene naphthalate) (PEN) substrates. These devices present a large-area graphene channel fully exposed to the external environment, in order to be suitable for sensing applications, and the channel conductivity is efficiently modulated by a buried gate contact under a thin Al2O3 insulating film. In order to be compatible with the use of the PEN substrate, optimized deposition conditions of the Al2O3 film by plasma-enhanced atomic layer deposition (PE-ALD) at a low temperature (100 °C) have been developed without any relevant degradation of the final dielectric performance.

Transcatheter arterial chemoembolization (TACE) in treatment of hepatocellular carcinoma.

BACKGROUND/AIMS: Substantial differences about the efficacy of transcatheter arterial chemoembolization for the treatment of hepatocellular carcinoma are reported in literature. This probably depends on the fact that in each single study, different patient selection criteria, type of epidemiological approach, end points adopted and kind of technical approach were used. This study aims to evaluate the efficacy of segmental transcatheter arterial chemoembolization in amelioring patient survival and to determine which patients might really benefit from this treatment. METHODOLOGY: To achieve our goals 193 consecutive patients (110 treated and 83 untreated) were studied. They were selected in the same period of time and matched as far as their demographic and clinical characteristics. RESULTS: Our results demonstrate that both in treated and control patients, Child class, alpha-fetoprotein and tumor diameter significantly influenced survival, resulting important prognostic factors. Transcatheter arterial chemoembolization significantly ameliorated survival in treated patients compared to controls (p < 0.0001). CONCLUSIONS: Transcatheter arterial chemoembolization significantly ameliorates survival in patients with hepatocellular carcinoma. However, the presence of large tumors producing high alpha-fetoprotein levels in patients with advanced Child class should discourage treatment.