Use Of Motion Sensors Research Articles

Sports activity (SA) recognition based on error correcting output codes (ECOC) and convolutional neural network (CNN)

The increasing use of motion sensors is causing major changes in the process of monitoring people's activities. One of the main applications of these sensors is the detection of sports activities, for example, they can be used to monitor the condition of athletes or analyze the quality of sports training. Although the existing sensor-based activity recognition systems can recognize basic activities such as: walking, running, or sitting; they don't perform well in recognizing different types of sports activities. This article introduces a new model based on machine learning (ML) techniques to more accurately distinguish between sports and everyday activities. In the proposed method, the necessary data to detect the type of activity is collected through his two sensors: an accelerometer and a gyroscope attached to a person's foot. For this purpose, the input signals are first preprocessed and then short-time Fourier transform (STFT) is used to describe the characteristics of each signal. In the next step, each STFT matrix is used as input to a convolutional neural network (CNN). This CNN describes various motion characteristics of the sensor in the form of vectors. Finally, a classification model based on error correction output code (ECOC) is used to classify the extracted features and detect the type of SA. The performance of the proposed AS recognition method is evaluated using the DSADS database and the results are compared with previous methods. Based on the results, the proposed method can recognize sports activities with an accuracy of 99.71. Furthermore, the performance of the proposed method based on precision and recall criteria are 99.72 and 99.71, respectively, which are better than the compared methods.

Using open surgery simulation kinematic data for tool and gesture recognition.

The use of motion sensors is emerging as a means for measuring surgical performance. Motion sensors are typically used for calculating performance metrics and assessing skill. The aim of this study was to identify surgical gestures and tools used during an open surgery suturing simulation based on motion sensor data. Twenty-five participants performed a suturing task on a variable tissue simulator. Electromagnetic motion sensors were used to measure their performance. The current study compares GRU and LSTM networks, which are known to perform well on other kinematic datasets, as well as MS-TCN++, which was developed for video data and was adapted in this work for motion sensors data. Finally, we extended all architectures for multi-tasking. In the gesture recognition task the MS-TCN++ has the highest performance with accuracy of [Formula: see text] and F1-Macro of [Formula: see text], edit distance of [Formula: see text] and F1@10 of [Formula: see text] In the tool usage recognition task for the right hand, MS-TCN++ performs the best in most metrics with an accuracy score of [Formula: see text], F1-Macro of [Formula: see text], F1@10 of [Formula: see text], and F1@25 of [Formula: see text]. The multi-task GRU performs best in all metrics in the left-hand case, with an accuracy of [Formula: see text], edit distance of [Formula: see text], F1-Macro of [Formula: see text], F1@10 of [Formula: see text], and F1@25 of [Formula: see text]. In this study, using motion sensor data, we automatically identified the surgical gestures and the tools used during an open surgery suturing simulation. Our methods may be used for computing more detailed performance metrics and assisting in automatic workflow analysis. MS-TCN++ performed better in gesture recognition as well as right-hand tool recognition, while the multi-task GRU provided better results in the left-hand case. It should be noted that our multi-task GRU network is significantly smaller and has achieved competitive results in the rest of the tasks as well.

Methods for physical activity evaluation among the working population

The high incidence of physical inactivity in the last decades increases the need for development and use of lifestyle interventions that promote physical activity, especially among the working population. The levels of occupational and leisure time physical activity differ and are specific among workers form different occupations, often creating opposing health effects or the so called “physical activity health paradox”. The aim of this paper is to present different methods for physical activity evaluation, and to determine the best methodological approach for the evaluation of the physical activity and its domains among the working population. Through literature review, the most common methods for physical activity evaluation among the working population are shown: subjective (interview, self-reported questionnaires and physical activity logs), objective (measurement of energy expenditure, physiological measurements, use of motion sensors) and combined methods (subjective-objective). Criteria for selection of corresponding methodological approach for physical activity evaluation among the working population are discussed, including the characteristics of the examined population and the used methods (quality, objectivity, level of work load, cost-effectiveness, specific limitations). The obtained data will help create recommendations for interventions for health promotion among the working population.

Review of Motion Sensors as a Home Security System and approach to the Internet of Things Project

Home security is an essential factor and must be maintained; currently, the development of technology or security systems continues to be improved, one of which is Eye Retina and Artificial Intelligence. in this research, the use of Motion Sensors in Home Security, performance evaluation, and future development. In this time, more crimes occur in our environment, one of which is theft or breaking into people's homes in various areas; this problem is disturbing to residents in areas where these crimes often occur, even though so far, residents have used many methods to prevent crime, one of which is installing CCTV. However, thieves still have managed to escape the CCTV surveillance. But suppose we use a security system that can make a sound. In that case, the sound can make criminals cancel their intention to steal because the sound disturbs their concentration and can also wake the house owner or tell residents about a crime in the house. And in this article, I will describe a home security system. This system requires several supporting equipment, such as PIR, Arduino, Buzzer, and other tools.

Input estimation of nonlinear systems using probabilistic neural network

Input estimation is an involved task with wide applications in nonlinear dynamic systems. Model-based input estimation methods are not feasible solutions for problems in which the underlying behavior is not sufficiently known. Data-driven methods have recently shown promise in capturing hidden and subtle nonlinearities in problems from various domains. In this study, we introduce a machine learning approach for input estimation of nonlinear dynamic systems that is applicable for a variety of mechanical properties and system complexities. The proposed neural regression model enables uncertainty quantification in predictions for each time sample which is a novel and helpful tool to analyze the accuracy of the results. For verification, three applications are investigated: (a) a numerical quarter-car model, (b) a real-world building, and (c) a real-world vehicle suspension system. We show that the estimated input signals in a numerically modeled system and real-world dynamic systems closely follow the actual inputs. In particular, the efficacy of input estimations in real-world cases confirms the strength of the proposed approach for similar applications with significant impact. For instance, the findings of this work enables the use of motion sensors mounted inside the vehicles for bridge vibration data collection which is proposed as a scalable and inexpensive paradigm for assessment of transportation infrastructure.

WEB-BASED SCHEDULING APPLICATION AND MOTION SENSOR USING ARDUINO MEGA

The purpose of this research is to find out how to make a web application that can control electronic devices in the building, find out how to make motion sensor circuits with Arduino Mega, electronic devices can be on or off, and find out which one is more efficient in using web applications and sensors. motion on the building. The results of this study indicate that the creation of a web scheduling application that can control the needs of building electronic equipment: webserver (hosting), internet connection, Ethernet shield, Arduino mega, relay module, and the use of motion sensors with Arduino Mega. which can adjust the sensitivity and time delay of signaling when there is the movement of a human object. The use of Ethernet shield and motion sensor each has advantages and disadvantages. It would be better if the two components were combined.

Economic Efficiency Of Implementation Of Lighting control In Public Buildings

The article is devoted to the description of experimental studies of the possibility of increasing the energy efficiency of the lighting installation (LI) through the use of motion sensors. Data on possible energy savings are needed to conduct economic calculations – to estimate the payback period of capital costs for the implementation of a lighting control system (LCS). A quantitative and qualitative assessment of the economic feasibility of creating or developing an LCS is based on calculating and analyzing the costs required for its implementation and comparing the costs with the results obtained during its implementation. The results of the functioning of the LCS can be expressed by such a value as the percentage of possible energy savings, expressed in terms of the ratio of electricity consumption after the introduction of the LCS to the consumption of electricity before its implementation. In this work, this coefficient was determined experimentally. The experiment was carried out in public building – in the laboratory and educational building of the university. A corridor of one of the floors was chosen as the object of the study. For the research, a data collection system based on a digital microcontroller was used; infrared motion sensors were usedas presence sensors. The results of the experiment showed that the presence of people in the corridor varies during the day, by days of the week, from month to month. Studies have shown that, on average, energy savings when using motion sensors in the on / off mode of lamps is at least 50 %. With an increase in the delay time for turning off the luminaires after the motion sensor is triggered, the energy saving decreases from 66.5 % to 48.5 %. When using the standby lighting mode during the absence of people, the savings are reduced from 66.5 % (with the lamps turned off due to lack of movement) to 21.9 %.

425 - Do seniors find sensors use for assessment and surveillance of cognitive functioning acceptable? Findings from two feasibility studies

Background Mild Cognitive Impairment is an at-risk stage for dementia and early detection has been increasingly recommended to facilitate beneficial interventions and forward planning. Changes in cognition and function can be insidious. In ageing populations, relying on relatives to detect changes is not sustainable. Moreover, resource scarcity necessitates that we innovate to find less manpower dependent methods for early detection and assessment.Objectives In two separate feasibility studies, we set out to evaluate if sensors could be utilized to (1) detect changes in behaviour patterns in homes of community dwelling elderly* & (2) evaluate instrumental activities of daily living (iADLs) in a smart home lab setting.Method In the first study, 59 community-dwelling seniors (aged >65 years) were observed over the course of 2 months through the use of motion sensors, smart plugs, bed sensors and activity bands. Behaviour metrics such as forgetfulness, outings and sleep were tracked. In the second study, a smart lab was equipped with similar sensors and 35 seniors were tasked to complete two iADLs (using the telephone and counting money) while being evaluated by the sensor system.Results In both studies, we found that it was feasible and seniors found the sensors to be acceptable. Over 80% of seniors had positive feedback for the in-home system and over 95% of seniors had found the lab-based evaluation of iADLs to be acceptable.Conclusion Sensor technology and smart homes are feasible to utilize for assessment and monitoring of cognition and function. Knowing that seniors find it acceptable is a crucial initial step. Much more needs to be done to refine the systems and the clinical information it yields.

Motion Sensor Application on Building Lighting Installation for Energy Saving and Carbon Reduction Joint Crediting Mechanism

Although common in developed countries such as Japan and Taiwan, the use of lamps coupled with motion sensors are still uncommon and even rare in Indonesia. Our experiment aims to show that simple installation of commercially available motion sensors can contribute to reduce the electricity bill from the increase of energy efficiency, abundance in availability of energy being the main factor in Indonesian high energy consumption habits. High electricity demand for consumption at current supply level in Indonesia led to the rising cost of electricity bills. This factor is compounded by the fact that many electric generators in Indonesia still use fossil fuels, which contributes to the high basic generation cost. UBL is one of the universities that aim to be a green campus. Our research explores the possibility of installing motion sensors to contribute to the energy efficiency. Although mostly common in developed countries, the use of motion sensors for energy efficiency is still rare, especially in Indonesia. Despite rising cost and supply shortages, Indonesian buildings are still of high energy consumption. Our experiment shows that simple installation of commercially available motion sensors can contribute to reduce the electricity bill from the increase of energy efficiency. One of the efforts to lower energy demand on the consumer side is to use the electricity efficiently, such as turning off lights in a room when it is not in use. This method can be simply done by turning the light switches for office and classrooms, but difficult to do in public spaces such as toilets and corridors. Automatic light switches experimentally installed in sample toilet rooms prove that electricity consumption from the lamps can contribute to the reduction of total weekly energy that translates into Greenhouse Gas emission reduction.

Coherence between self-reported and objectively measured physical activity in patients with chronic obstructive lung disease: a systematic review.

The beneficial effects of physical activity (PA) in patients with COPD, as well as the methods of their assessment, are well known and described. As objective measures of PA, such as the use of motion sensors, video recordings, exercise capacity testing, and indirect calorimetry, are not easily obtained in the daily clinical life, the reliability of the more accessible self-reported measurements of PA is important. In this review, we systematically identified original studies involving COPD patients and at least one parameter of self-reported and objective exercise testing, and analyzed every article for coherence between the objectively and self-reported measured PA. The studies are few, small, and very diverse, both in their use of questionnaires and objective measurements. Self-reported assessments were found to generally overestimate the level of PA compared to measurements made objectively by activity monitors; however, more studies are needed to rely solely on the use of PA questionnaires in COPD patients. The most accurate and valid questionnaires appear to be the self-completed Physical Activity Scale for the Elderly and the interviewer-completed Stanford Seven-Day Physical Activity Recall Questionnaire, but the ideal questionnaire still awaits construction. The motion sensors are accurate and validated in this patient group, especially SenseWear™, but not easily accessible in clinical practice, as they have various technical and adhesive difficulties.

Luna Park (2011): An Aesthetics of Shock

In 2011, Greek composer Georges Aperghis was commissioned by IRCAM to compose Luna Park, a key work in his output that deals with the themes of video-surveillance. Involving dance-like gestures, flutes, video projections, and motion sensors, the composer found a new path for artistic expression through multimedia. Georges Aperghis is one of the leading composers of Contemporary Music Theatre. Already well known for his a series of works composed for the Avignon Festival [Salzman, E., & Desi, T. (2008). The new music theatre: Seeing the voice, hearing the body. Oxford: Oxford University Press], he has built a multi-disciplinary practice, combining comedians, dancers, and instrumentalists within ambitious projects (Commentaires in 1996, Avis de Tempête and Machinations in 2000). Following the different stages of the creation and realisation of the piece, one is struck by a crucial fact: there is no score. We will demonstrate how Georges Aperghis created the work in a process of selection and combination, gradually arriving at the final structure. The visual dimensions of this work are particularly significant, including gestures that are amplified with the use of motion sensors. But how can we understand the structure of a piece where gestures can have as much as structural power than music? The aim of this paper is to analyse Luna Park using material in IRCAM’s archive: interviews, photos, films, as well as the software and hardware used in the performance. Invoking Benjamin’s concept of ‘schock’, the authors will show how these features convey a multi-layered and multi-modal aesthetic perception from the local to the global form. The essay is illustrated by a video of the performance, with dynamic meta-data highlighting these multi-layered aesthetic and semantic dimensions.

Older Adults' and Caregivers' Perspectives on In-Home Monitoring Technology.

In the past decade, there has been an increase in the application and investigation of in-home monitoring systems to support older adults with dementia and their caregivers. The current study focused on a monitoring system that included the use of motion sensors and Internet connections with one-way communication capabilities. Only a limited number of studies have explored and compared older adults' and caregivers' perspectives on such monitoring systems. The purpose of the current study was to explore older adults' and caregivers' perspectives on in-home monitoring systems using photo elicitation techniques. Three overarching themes emerged: (a) feeling cared for (which included two sub-themes), (b) feeling cared about (which included three sub-themes), and (c) suggestions for change (which included four sub-themes). These results revealed the duality of care when using in-home monitoring. Clinical and other future implications are discussed. [Journal of Gerontological Nursing, 42(6), 43-50.].

Respiration Disorders Classification With Informative Features for m-Health Applications.

Respiratory disorder is a highly prevalent condition associated with many adverse health problems. As the current means of diagnosis are obtrusive and ill-suited for real-time m-health applications, we explore a convenient and low-cost automatic approach that uses wearable microelectromechanical system sensor technology. The proposed system introduces the use of motion sensors to detect the changes in the anterior-posterior diameter of the chest wall during breathing function as well as extracting the informative respiratory features to be used for breathing disorders classification. Extensive evaluations are provided on six well-known classifiers with novel feature extraction techniques to distinguish among eight different pathological breathing patterns. The effects of the number of sensors, sensor placement, as well as feature selection on the classification performance are discussed. The experimental results conducted with ten subjects show the best accuracy rates of 97.50% by support vector machine and 97.37% with decision tree bagging (DTB) with all features and after feature selection, correspondingly. Furthermore, a binary classification is proposed for distinguishing between healthy people and patients with breath problems. The different assessments of classification parameters are provided by measuring the accuracy, sensitivity, specificity, F1-score and Mathew correlation coefficient. The accuracy rates above 98% suggest superior performance of DTB in binary recognition supported by the suggested new features.

Promising Projects of Energy Saving in Housing and Communal Services of Ukraine

The article analyses the projects that help conserve energy for general use (lighting staircase, entrances to the staircases) in apartment buildings of the city district. It is established that a promising project, which provides power savings is the use of motion sensors and led lamps. The project allows to save hundreds of thousands of kilowatts of electricity and to ensure its efficient use. It reduces the load on the internal electrical network (especially in winter) and the rent for the residents of the apartments. The pilot project of involving the application of nanolamps in housing and communal sphere deserves a lot of attention. They put lighting on a new energy efficient level, compared to existing led lamps. Nano bulbs provide uniform light distribution and maximum coverage. The frequency of switching on and off does not affect their functional characteristics. During operation they emit 50% less heat than led lamps and are safer for use in enclosed fixtures (devices).

A Basic Study on Implementing Optimal Function of Motion Sensor for Bridge Navigational Watch Alarm System

A Bridge Navigational Watch Alarm System (hereafter 'BNWAS') is to monitor and detect if an officer of watch(hereafter ‘OOW’) keeps a sharp lookout on the bridge. The careless lookout of an OOW could lead to marine accidents. For this reason on June 5th, 2009, IMO decided that a ship is equipped with a BNWAS. However, an existing BNWAS gives the OOW a lot of inconvenience and stress in its operation. It requires that the OOW should press reset buttons to confirm their alert watch on the bridge at every three to twelve minute. Many OOWs have complained that at some circumstances they cannot focus on their bridge activities including watch-keeping due to a lots of resetting inputs of BNWAS. Accordingly, IMO has allowed the use of a motion sensor as a resetting device. The motion sensor detects the movements of human body on the bridge and subsequently sends reset signals directly to BNWAS automatically. As a result, OOWs can work uninterrupted. However, some of classification societies and flag authorities have a slightly different stance on the use of motion sensor as a resetting method for BNWAS. The reason is that the motion sensor may trigger false reset signals caused by the motion of objects on the bridge, especially a slight movement such as toss and turn of human body which can extend the period of careless watch. As a basic study to minimize the false reset signals, this paper proposes a simple configuration of BNWAS, which consists of only three motion sensors associated with ‘AND’ and ‘OR’ logic gates. Additionally, several considerations are also proposed for the implementation of motion sensors. This study found that the proposed configuration which consists of three motion sensors is better than an existing one by reducing false reset signals caused by a slight movement of human body in one’s sleep. The proposed configuration in this paper filters false reset signals and is simple to be implemented on existing vessels. In addition, it can be easily installed just by a basic electrical knowledge.

On the Best Sensor for Keystrokes Inference Attack on Android

Abstract One of the most recently exposed security threats on smartphone platforms is the potential use of motion sensors to infer user keystrokes. Exploited as side channels, few researchers have demonstrated the ability of built-in accelerometers and gyroscopes in particular, to reveal information related to user input, though the practicality of such an attack remains an open question. This paper takes further steps along the path of exploring the aspects of the new threat, addressing the question of which available sensors can perform best in the context of the inference attack. We design and implement a benchmark experiment, against which the performances of several commodity smartphone-sensors are compared, in terms of inference accuracy. All available Android motion sensors are considered through different settings provided by the OS, and we add the option of fusing several sensors input into a single dataset, to examine the amount/lack of improvement in the attack accuracy. Our results indicate an outstanding performance of the gyroscope sensor, and the potential improvement obtained out of sensors data fusion. On the other hand, it seems that sensors with magnetometer component or the accelerometer alone have less benefit in the adverted attack.

Measurement of Physical Activity by Self-Report in Low- and Middle-Income Countries: More of the Same Is not Enough

In spite of the growing use of motion sensors, particularly accelerometers, for the measurement of physical activity in high-income countries,1 virtually all population-based physical activity studies from lowand middle-income countries (LMICs) still rely on selfreport.2,3 In addition to the well known financial aspect of this inequality, availability of trained personnel is another challenge in LMICs. Also, less widely known barriers, such as importation regulations also play a role.4 The measurement of physical activity in LMICs is particularly challenging. First, literacy issues need to be taken into account; low literacy makes self-administration of instruments in population-based samples virtually impossible. Second, the low coverage of telephone lines in several areas makes it unfeasible to conduct phone survey; for example, the Brazilian phone surveillance system takes place in state capitals only. Third, internet access is still a luxury in several parts of the world, and therefore, computer-based instruments are unlikely to be appropriate for large scale studies in LMICs.5 Over the last years, a series of papers tried to highlight underlying principles of physical activity measurement. However, most were developed in high-income countries and very little was said on the measurement of physical activity in LMICs. Some aspects that deserve special consideration are

Method for measuring violin sound radiation based on bowed glissandi and its application to sound synthesis

This work presents a method for measuring and computing violin-body directional frequency responses, which are used for violin sound synthesis. The approach is based on a frame-weighted deconvolution of excitation and response signals. The excitation, consisting of bowed glissandi, is measured with piezoelectric transducers built into the bridge. Radiation responses are recorded in an anechoic chamber with multiple microphones placed at different angles around the violin. The proposed deconvolution algorithm computes impulse responses that, when convolved with any source signal (captured with the same transducer), produce a highly realistic violin sound very similar to that of a microphone recording. The use of motion sensors allows for tracking violin movements. Combining this information with the directional responses and using a dynamic convolution algorithm, helps to improve the listening experience by incorporating the violinist motion effect in stereo.

Measuring Physical Activity and Sedentary Behaviors in Women with Young Children: A Systematic Review

Current evidence indicates that women with young children are less active than women without children. In this review the authors investigated the methods of measuring physical activity employed in studies of women with young children (aged 1–5 years) and the associated challenges in measurement. Articles from databases (MEDLINE, OVID, CINAHL, Google Scholar) and manual searches were limited to English peer-reviewed journals published from 1990 to 2010. Studies that included measurement of physical activity in samples of women with young children were selected. Measurement properties were extracted, and original reliability and validity articles were reviewed for physical activity measurement tools used by 15 samples. The evidence base was dominated by self-report measurement tools, many of which assessed leisure-time physical activity only. Use of motion sensors to assess physical activity in this population was limited. It is likely that much of the habitual physical activity performed by women with young children has not been captured by self-report measures. Further investigation should be undertaken using tools that capture adequately all health-enhancing physical activity among women with young children.

“Smart Homes” for Patients at the End of Life

Smart homes are residential settings equipped with sensors and other devices that enable the monitoring of residents, aiming to improve residents' quality of life and support their independence. Numerous initiatives worldwide have been developed to explore the use of motion sensors, radio frequency sensors, video cameras, wearable devices, and other applications that target older adults. As people approach the end of their lives, such settings may have the potential to support quality of life. This article presents existing smart home applications and discusses their potential for home hospice patients and their families. The concept of obtrusiveness of home technologies is reviewed and ethical considerations are discussed, such as a potential over-reliance on automation, the “medicalization” of the home environment (which may turn the residential setting into a “de-facto intensive care unit”), issues of privacy and security, and the challenge of informed consent for residents.