Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data

Smart homes for the aging population have recently started attracting the attention of the research community. The "health state" of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario.

Integrating optical fiber force sensors into microforceps for ORL microsurgery

The delicate anatomy of the ear require surgeons to use great care when operating on its internal structures. One example for such an intervention is the stapedectomy, where a small crook shaped piston is placed in the oval window of the cochlea and connected to the incus through crimping thus bypassing the diseased stapes. Performing the crimp process with the correct force is necessary since loose crimps poorly transmit sound whereas tight crimps will eventually result in necrosis of the incus. Clinically, demand is high to reproducibly conduct the crimp process through a precise force measurement. For this reason, we have developed a fiber Bragg grating (FBG) integrated microforceps for use in such interventions. This device was calibrated, and tested in cadaver preparations. With this instrument we were able to measure for the first time forces involved in crimping a stapes prosthesis to the incus. We also discuss a method of attaching and actuating such forceps in conjunction with a robot currently under development in our group. Each component of this system can be used separately or combined to improve surgical accuracy, confidence and outcome.

PM(10) remote sensing from geostationary SEVIRI and polar-orbiting MODIS sensors over the complex terrain of the European Alpine region

The subject of this study is to investigate the capability of spaceborne remote sensing data to predict ground concentrations of PM10 over the European Alpine region using satellite derived Aerosol Optical Depth (AOD) from the geostationary Spinning Enhanced Visible and InfraRed Imager (SEVIRI) and the polar-orbiting MODerate resolution Imaging Spectroradiometer (MODIS). The spatial and temporal resolutions of these aerosol products (10 km and 2 measurements per day for MODIS, ∼ 25 km and observation intervals of 15 min for SEVIRI) permit an evaluation of PM estimation from space at different spatial and temporal scales. Different empirical linear relationships between coincident AOD and PM10 observations are evaluated at 13 ground-based PM measurement sites, with the assumption that aerosols are vertically homogeneously distributed below the planetary Boundary Layer Height (BLH). The BLH and Relative Humidity (RH) variability are assessed, as well as their impact on the parameterization. The BLH has a strong influence on the correlation of daily and hourly time series, whilst RH effects are less clear and smaller in magnitude. Despite its lower spatial resolution and AOD accuracy, SEVIRI shows higher correlations than MODIS (rSEV∼ 0.7, rMOD∼ 0.6) with regard to daily averaged PM10. Advantages from MODIS arise only at hourly time scales in mountainous locations but lower correlations were found for both sensors at this time scale (r∼ 0.45). Moreover, the fraction of days in 2008 with at least one satellite observation was 27% for SEVIRI and 17% for MODIS. These results suggest that the frequency of observations plays an important role in PM monitoring, while higher spatial resolution does not generally improve the PM estimation. Ground-based Sun Photometer (SP) measurements are used to validate the satellite-based AOD in the study region and to discuss the impact of aerosols' micro-physical properties in the empirical models. A lower error limit of 30 to 60% in the PM10 assessment from space is estimated in the study area as a result of AOD uncertainties, variability of aerosols properties and the heterogeneity of ground measurement sites. It is concluded that SEVIRI has a similar capacity to map PM as sensors on board polar-orbiting platforms, with the advantage of a higher number of observations. However, the accuracy represents a serious limitation to the applicability of satellites for ground PM mapping, especially in mountainous areas.

A smart multi-hop hierarchical routing protocol for efficient video communication over wireless multimedia sensor networks

For smart applications, nodes in wireless multimedia sensor networks (MWSNs) have to take decisions based on sensed scalar physical measurements. A routing protocol must provide the multimedia delivery with quality level support and be energy-efficient for large-scale networks. With this goal in mind, this paper proposes a smart Multi-hop hierarchical routing protocol for Efficient VIdeo communication (MEVI). MEVI combines an opportunistic scheme to create clusters, a cross-layer solution to select routes based on network conditions, and a smart solution to trigger multimedia transmission according to sensed data. Simulations were conducted to show the benefits of MEVI compared with the well-known Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol. This paper includes an analysis of the signaling overhead, energy-efficiency, and video quality.

Eluding oblivion with smart stochastic selection of synaptic updates

The variables involved in the equations that describe realistic synaptic dynamics always vary in a limited range. Their boundedness makes the synapses forgetful, not for the mere passage of time, but because new experiences overwrite old memories. The forgetting rate depends on how many synapses are modified by each new experience: many changes means fast learning and fast forgetting, whereas few changes means slow learning and long memory retention. Reducing the average number of modified synapses can extend the memory span at the price of a reduced amount of information stored when a new experience is memorized. Every trick which allows to slow down the learning process in a smart way can improve the memory performance. We review some of the tricks that allow to elude fast forgetting (oblivion). They are based on the stochastic selection of the synapses whose modifications are actually consolidated following each new experience. In practice only a randomly selected, small fraction of the synapses eligible for an update are actually modified. This allows to acquire the amount of information necessary to retrieve the memory without compromising the retention of old experiences. The fraction of modified synapses can be further reduced in a smart way by changing synapses only when it is really necessary, i.e. when the post-synaptic neuron does not respond as desired. Finally we show that such a stochastic selection emerges naturally from spike driven synaptic dynamics which read noisy pre and post-synaptic neural activities. These activities can actually be generated by a chaotic system.

Annexins as intracellular calcium sensors

The annexins are a multigene family of Ca(2+)- and charged phospholipid-binding proteins. Although they have been ascribed with diverse functions, there is no consensus about the role played by this family as a whole. We have mapped the Ca(2+)-induced translocations of four members of the annexin family and of two truncated annexins in live cells, and demonstrated that these proteins interact with the plasma membrane as well as with internal membrane systems in a highly coordinated manner. Annexin 2 was the most Ca(2+) sensitive of the studied proteins, followed by annexins 6, 4 and 1. The calcium sensitivity of annexin 2 increased further following co-expression with S100A10. Upon elevation of [Ca(2+)](i), annexins 2 and 6 translocated to the plasma membrane, whereas annexins 4 and 1 also became associated with intracellular membranes and the nuclear envelope. The NH(2)-terminus had a modulatory effect on plasma membrane binding: its truncation increased the Ca(2+) sensitivity of annexin 1, and decreased that of annexin 2. Given the fact that several annexins are present within any one cell, it is likely that they form a sophisticated [Ca(2+)] sensing system, with a regulatory influence on other signaling pathways.

Minimized cardiopulmonary bypass combined with a smart suction device: the future of cardiopulmonary bypass?

OBJECTIVE: The standard heart-lung machine is a major trigger of systemic inflammatory response and the morbidity attributed to conventional extracorporeal circulation (CECC) is still significant. Reduction of blood-artificial surface contact and reduction of priming volume are principal aims in minimized extracorporeal circulation (MECC) cardiopulmonary bypass systems. The aim of this paper is to give an overview of the literature and to present our experience with the MECC-smart suction system. METHODS AND RESULTS: At our institution, 1799 patients underwent isolated coronary artery bypass grafting (CABG) surgery, 1372 with a MECC-smart suction system and 427 with CECC. All in-hospital data were assessed and the results were compared between the 2 groups. Patient characteristics and the distribution of EuroSCORE risk profile in our collective were similar between both groups. Average age in the MECC collective was 67.5 +/- 11.4 years and average EuroSCORE was 5.0 +/- 1.5. Average number of distal anastomoses was similar to the average number encountered in patients undergoing CABG surgery with CECC (3.3 +/- 1.0 for MECC versus 3.2 +/- 1.1 for CECC; P = ns). Myocardial protection is superior in MECC patients with lower postoperative maximal cTnI values (11.0 +/- 10.8 micromol/L for MECC versus 24.7 +/- 25.3 micromol/L for CECC; P < .05). Postoperative recovery was faster in patients operated on with the MECC-smart suction system and discharge from the hospital was earlier than for CECC patients (7.4 +/- 1.9 days for MECC versus 8.8 +/- 3.8 days for CECC; P < .05). CONCLUSIONS: The MECC-smart suction system is a safe perfusion technique for CABG surgery. In patients operated on with this system, the clinical outcome seems to be better than in patients operated on with CECC. This promising and less damaging perfusion technology has the potential to replace CECC systems in CABG surgery.

Clinical validation of electromyography and acceleromyography as sensors for muscle relaxation

BACKGROUND AND OBJECTIVE: The aim of this study was to determine which of two clinically applied methods, electromyography or acceleromyography, was less affected by external disturbances, had a higher sensitivity and which would provide the better input signal for closed loop control of muscle relaxation. METHODS: In 14 adult patients, anaesthesia was induced with intravenous opioids and propofol. The response of the thumb to ulnar nerve stimulation was recorded on the same arm. Mivacurium was used for neuromuscular blockade. Under stable conditions of relaxation, the infusion-rate was decreased and the effects of turning the hand were investigated. RESULTS: Electromyography and acceleromyography both reflected the change of the infusion rate (P = 0.015 and P < 0.001, respectively). Electromyography was significantly less affected by the hand-turn (P = 0.008) than acceleromyography. While zero counts were detected with acceleromyography, electromyography could still detect at least one count in 51.1%. CONCLUSIONS: Electromyography is more reliable for use in daily practice as it is less influenced by external disturbances than acceleromyography.

A Smart TCP Acknowledgment Approach for Multihop Wireless Networks

Reliable data transfer is one of the most difficult tasks to be accomplished in multihop wireless networks. Traditional transport protocols like TCP face severe performance degradation over multihop networks given the noisy nature of wireless media as well as unstable connectivity conditions in place. The success of TCP in wired networks motivates its extension to wireless networks. A crucial challenge faced by TCP over these networks is how to operate smoothly with the 802.11 wireless MAC protocol which also implements a retransmission mechanism at link level in addition to short RTS/CTS control frames for avoiding collisions. These features render TCP acknowledgments (ACK) transmission quite costly. Data and ACK packets cause similar medium access overheads despite the much smaller size of the ACKs. In this paper, we further evaluate our dynamic adaptive strategy for reducing ACK-induced overhead and consequent collisions. Our approach resembles the sender side's congestion control. The receiver is self-adaptive by delaying more ACKs under nonconstrained channels and less otherwise. This improves not only throughput but also power consumption. Simulation evaluations exhibit significant improvement in several scenarios