Interoperable services based on activity monitoring in ambient assisted living environments

Ambient Assisted Living (AAL) is considered as the main technological solution that will enable the aged and people in recovery to maintain their independence and a consequent high quality of life for a longer period of time than would otherwise be the case. This goal is achieved by monitoring human’s activities and deploying the appropriate collection of services to set environmental features and satisfy user preferences in a given context. However, both human monitoring and services deployment are particularly hard to accomplish due to the uncertainty and ambiguity characterising human actions, and heterogeneity of hardware devices composed in an AAL system. This research addresses both the aforementioned challenges by introducing 1) an innovative system, based on Self Organising Feature Map (SOFM), for automatically classifying the resting location of a moving object in an indoor environment and 2) a strategy able to generate context-aware based Fuzzy Markup Language (FML) services in order to maximize the users’ comfort and hardware interoperability level. The overall system runs on a distributed embedded platform with a specialised ceiling- mounted video sensor for intelligent activity monitoring. The system has the ability to learn resting locations, to measure overall activity levels, to detect specific events such as potential falls and to deploy the right sequence of fuzzy services modelled through FML for supporting people in that particular context. Experimental results show less than 20% classification error in monitoring human activities and providing the right set of services, showing the robustness of our approach over others in literature with minimal power consumption

Si elegans: a computational model of C. elegans muscle response to light

It has long been the goal of computational neuroscientists to understand animal nervous systems, but their vast complexity has made it very difficult to fully understand even basic functions such as movement. The C. elegans nematode offers the opportunity to study a fully described connectome and link neural network to behaviour. In this paper a model of the responses of the body wall muscle in C. elegans to a random light stimulus is presented. An algorithm has been developed that tracks synapses in the nematode nervous system from the stimulus in the phototaxis sensory neurons to the muscles cells. A linear second order model was used to calculate the isometric force in each of the C. elegans body wall muscle cells. The isometric force calculated resembles that of previous investigations in muscle modelling

Human behavioural analysis with self-organizing map for ambient assisted living

This paper presents a system for automatically classifying the resting location of a moving object in an indoor environment. The system uses an unsupervised neural network (Self Organising Feature Map) fully implemented on a low-cost, low-power automated home-based surveillance system, capable of monitoring activity level of elders living alone independently. The proposed system runs on an embedded platform with a specialised ceiling-mounted video sensor for intelligent activity monitoring. The system has the ability to learn resting locations, to measure overall activity levels and to detect specific events such as potential falls. First order motion information, including first order moving average smoothing, is generated from the 2D image coordinates (trajectories). A novel edge-based object detection algorithm capable of running at a reasonable speed on the embedded platform has been developed. The classification is dynamic and achieved in real-time. The dynamic classifier is achieved using a SOFM and a probabilistic model. Experimental results show less than 20% classification error, showing the robustness of our approach over others in literature with minimal power consumption. The head location of the subject is also estimated by a novel approach capable of running on any resource limited platform with power constraints

Treatment of urinary schistosomiasis: methodological issues and research needs identified through a Cochrane systematic review

SUMMARY Guidelines recommend praziquantel (PZQ) for the treatment and control of schistosomiasis, with no real alternative. Metrifonate was still widely used against Schistosoma haematobium in the 1990s, and then withdrawn. Experimental studies and clinical trials suggest that artemisinin compounds are active against S. haematobium. In a Cochrane systematic review assessing the efficacy and safety of drugs for treating urinary schistosomiasis, 24 randomized controlled trials (n=6315 individuals) met our inclusion criteria. These trials compared a variety of single agent and combination regimens with PZQ, metrifonate or artemisinin derivatives. The review confirmed that both the standard recommended doses of PZQ (single 40 mg/kg oral dose) and metrifonate (3×7·5-10 mg/kg oral doses administered fortnightly) are efficacious and safe in treating urinary schistosomiasis, but there is no study comparing these two regimens head-to-head. There is currently not enough evidence to evaluate artemisinin compounds. Most of the studies included in the Cochrane systematic review were insufficiently powered, lacked standardization in assessing and reporting outcomes, and had a number of methodological limitations. In this paper we discuss the implications of these findings with respect to public health and research methodology and propose priority research needs

Assessment of Customer Expectation and Perception of Service Quality Delivery in Ghana Commercial Bank

The study is to determine customers\u27 expectations and perception of quality of servicedelivery of Ghana Commercial Banks Limited. The study also aims at determining thegap between customers\u27 expectation and perception of service quality delivery(customer satisfaction /dissatisfaction) of the banks. To achieve the main aim of thestudy, the following specific objectives have been set out; determine customers\u27expectations of the quality of service delivery of GCB, measure customers\u27 perceptionof the quality of service delivery of GCB, determine the gap (customer satisfaction ordissatisfaction) between customers\u27 perception and expectation of service qualitydelivery of the bank

A multi-level refinement approach towards the classification of quotidian activities using accelerometer data

Wearable inertial measurement units incorporating accelerometers and gyroscopes are increasingly used for activity analysis and recognition. In this paper an activity classification algorithm is presented which includes a novel multi-step refinement with the aim of improving the classification accuracy of traditional approaches. To do so, after the classification takes place, information is extracted from the confusion matrix to focus the computational efforts on those activities with worse classification performance. It is argued that activities differ diversely from each other, therefore a specific set of features may be informative to classify a specific set of activities, but such informativeness should not necessarily be extended to a different activity set. This approach has shown promising results, achieving important classification accuracy improvements of up to 4% with the use of low-dimensional feature vectors

Treatment of urinary schistosomiasis: methodological issues and research needs identified through a Cochrane systematic review

Guidelines recommend praziquantel (PZQ) for the treatment and control of schistosomiasis, with no real alternative. Metrifonate was still widely used against Schistosoma haematobium in the 1990s, and then withdrawn. Experimental studies and clinical trials suggest that artemisinin compounds are active against S. haematobium. In a Cochrane systematic review assessing the efficacy and safety of drugs for treating urinary schistosomiasis, 24 randomized controlled trials (n=6315 individuals) met our inclusion criteria. These trials compared a variety of single agent and combination regimens with PZQ, metrifonate or artemisinin derivatives. The review confirmed that both the standard recommended doses of PZQ (single 40 mg/kg oral dose) and metrifonate (3×7·5-10 mg/kg oral doses administered fortnightly) are efficacious and safe in treating urinary schistosomiasis, but there is no study comparing these two regimens head-to-head. There is currently not enough evidence to evaluate artemisinin compounds. Most of the studies included in the Cochrane systematic review were insufficiently powered, lacked standardization in assessing and reporting outcomes, and had a number of methodological limitations. In this paper we discuss the implications of these findings with respect to public health and research methodology and propose priority research need

Pesticidal Effects of Extracts from Hyptis suaveolens and Hyptis spicigera on Cowpea Weevils

This experimental research was conducted with the view of determining the effectiveness of Hyptis suaveolens and Hyptis spicigera extracts on cowpea seeds in deterring the feeding habit and life span of cowpea weevils. Masses of 400 and 500 grammes of pulverized samples of the two plants, Hyptis suaveolens and Hyptis spicigera were separately extracted by percolation with 2200 millilitres of 95% ethanol respectively. The percolates were evaporated to dryness at room temperature to give crude extracts of both plants which were each subjected to a partition process. Soluble solvent extracts of the two plants were applied on cowpea seeds and subjected to cowpea weevils by two-choice feeding deterrent method. The chloroform soluble extracts were found to be most active extracts of both plants with the least percentage consumption indices and higher percentage mortalities. This was a clear indication that these chloroform soluble extracts contained most of the toxic component(s) of the plants which can be used to protect cowpea seeds to some period of time. The study tasks the Ministry of Food and Agriculture to consider providing funding and further research into the use of the pesticides from these plant extracts to maintain the buoyancy of biodiversity as well as the environment in Ghana

Supporting independent living for older adults; employing a visual based fall detection through analysing the motion and shape of the human body

Falls are one of the greatest risks for older adults living alone at home. This paper presents a novel visual-based fall detection approach to support independent living for older adults through analysing the motion and shape of the human body. The proposed approach employs a new set of features to detect a fall. Motion information of a segmented silhouette when extracted can provide a useful cue for classifying different behaviours, while variation in shape and the projection histogram can be used to describe human body postures and subsequent fall events. The proposed approach presented here extracts motion information using best-fit approximated ellipse and bounding box around the human body, produces projection histograms and determines the head position over time, to generate 10 features to identify falls. These features are fed into a multilayer perceptron neural network for fall classification. Experimental results show the reliability of the proposed approach with a high fall detection rate of 99.60% and a low false alarm rate of 2.62% when tested with the UR Fall Detection dataset. Comparisons with state of the art fall detection techniques show the robustness of the proposed approach