Mobile Health App for Adolescents: Motion Sensor Data and Deep Learning Technique to Examine the Relationship between Obesity and Walking Patterns

With the prevalence of obesity in adolescents, and its long-term influence on their overall health, there is a large body of research exploring better ways to reduce the rate of obesity. A traditional way of maintaining an adequate body mass index (BMI), calculated by measuring the weight and height of an individual, is no longer enough, and we are in need of a better health care tool. Therefore, the current research proposes an easier method that offers instant and real-time feedback to the users from the data collected from the motion sensors of a smartphone. The study utilized the mHealth application to identify participants presenting the walking movements of the high BMI group. Using the feedforward deep learning models and convolutional neural network models, the study was able to distinguish the walking movements between nonobese and obese groups, at a rate of 90.5%. The research highlights the potential use of smartphones and suggests the mHealth application as a way to monitor individual health.

Using Sensor Graphs for Monitoring the Effect on the Performance of the OTAGO Exercise Program in Older Adults

The OTAGO exercise programme is effective in decreasing the risk for falls of older adults. This research investigated if there is an indication that the OTAGO exercise programme has a positive effect on the capacity and as well as on the performance in mobility. We used the data of the 10-months observational OTAGO pilot study with 15 (m = 1, f = 14) (pre-)frail participants aged 84.60 y (SD: 5.57 y). Motion sensors were installed in the flats of the participants and used to monitor their activity as a surrogate variable for performance. We derived a weighted directed multigraph from the physical sensor network, subtracted the weights of one day from a baseline, and used the difference in percent to quantify the change in performance. Least squares was used to compute the overall progress of the intervention (n = 9) and the control group (n = 6). In accordance with previous studies, we found indication for a positive effect of the OTAGO program on the capacity in both groups. Moreover, we found indication that the OTAGO program reduces the decline in performance of older adults in daily living. However, it is too early to conclude causalities from our findings because the data was collected during a pilot study.

Method for Estimating Temporal Gait Parameters Concerning Bilateral Lower Limbs of Healthy Subjects Using a Single In-Shoe Motion Sensor through a Gait Event Detection Approach

To expand the potential use of in-shoe motion sensors (IMSs) in daily healthcare or activity monitoring applications for healthy subjects, we propose a real-time temporal estimation method for gait parameters concerning bilateral lower limbs (GPBLLs) that uses a single IMS and is based on a gait event detection approach. To validate the established methods, data from 26 participants recorded by an IMS and a reference 3D motion analysis system were compared. The agreement between the proposed method and the reference system was evaluated by the intraclass correlation coefficient (ICC). The results showed that, by averaging over five continuous effective strides, all time parameters achieved precisions of no more than 30 ms and agreement at the “excellent” level, and the symmetry indexes of the stride time and stance phase time achieved precisions of 1.0% and 3.0%, respectively, and agreement at the “good” level. These results suggest our method is effective and shows promise for wide use in many daily healthcare or activity monitoring applications for healthy subjects.

ІНТЕЛЕКТУАЛЬНА СИСТЕМА УПРАВЛІННЯ В ОСВІТЛЕННІ ПІШОХІДНИХ ПЕРЕХОДІВ ДЛЯ ПІДВИЩЕННЯ ЕНЕРГОЕФЕКТИВНОСТІ

Purpose. Development of the concept of an intelligent control system for implementation in the scheme of pedestrian crossing lighting and design of a street lamp to reduces electricity costs and increases the service life of street lights, using technical devices such as dimmers and special motion sensors.Method. The research methods of theoretical analysis, modeling of appearance and creation of the scheme of intellectual control complex, basic provisions on lighting of pedestrian crossings and design of street lighting, analysis of possibilities of motion sensors and dimming at use in lighting are used.Results. Technologies of application of dimers and various motion sensors in lighting are analyzed and modern technological advantages of their use are allocated. Having identified a problem in the payment for electricity for street lighting for many local budgets, an intelligent control system for pedestrian crossing lighting was developed. The system allows obtaining of significant economic effect, reducing electricity consumption by a maximum of 70%. This saving is achieved by using dimming lamps and special narrow motion sensors, which have a viewing angle of 6 ° horizontally. At rest, the system keeps the lamp power at 50% until the person falls within the range of the sensor and the illumination rises to 100% for the set time. Specially selected sensors and their correct placement allow the system to work only when a person approaches a pedestrian crossing, and to remove accidental unpredictable inclusions. After analyzing the modern street lighting market, the design of a street lamp was created and proposed.Scientific novelty. It is proposed to use an intelligent control system in the lighting of pedestrian crossings, because now it is widely used only as part of the complex "smart home". Application in the scheme of lighting of pedestrian crossings of dimming and special narrowly directed motion sensors with a viewing angle of 6° horizontally that will allow to exclude accidental operation, both from people and cars, and from dogs and cats. A new design of the road lamp has been developed, based on the analyzed provisions on the correct lighting of pedestrian crossings.Practical significance. Lighting of pedestrian crossings is currently a problem in our country, because there are many accidents, and for good lighting you need to spend a lot of money on electricity from local budgets. This intelligent pedestrian crossing lighting control system is specially designed so that the use of electricity can be reduced by 70% and the service life of lamps can be significantly increased, for example by 1.5 times, but a more accurate value can be obtained only after the introduction of the first experimental sample. The use of such a system is possible throughout Ukraine at each crossing, unlike many other projects for lighting road crossings.

Towards Device Independent Eavesdropping on Telephone Conversations with Built-in Accelerometer

Motion sensors in modern smartphones have been exploited for audio eavesdropping in loudspeaker mode due to their sensitivity to vibrations. In this paper, we further move one step forward to explore the feasibility of using built-in accelerometer to eavesdrop on the telephone conversation of caller/callee who takes the phone against cheek-ear and design our attack Vibphone. The inspiration behind Vibphone is that the speech-induced vibrations (SIV) can be transmitted through the physical contact of phone-cheek to accelerometer with the traces of voice content. To this end, Vibphone faces three main challenges: i) Accurately detecting SIV signals from miscellaneous disturbance; ii) Combating the impact of device diversity to work with a variety of attack scenarios; and iii) Enhancing feature-agnostic recognition model to generalize to newly issued devices and reduce training overhead. To address these challenges, we first conduct an in-depth investigation on SIV features to figure out the root cause of device diversity impacts and identify a set of critical features that are highly relevant to the voice content retained in SIV signals and independent of specific devices. On top of these pivotal observations, we propose a combo method that is the integration of extracted critical features and deep neural network to recognize speech information from the spectrogram representation of acceleration signals. We implement the attack using commodity smartphones and the results show it is highly effective. Our work brings to light a fundamental design vulnerability in the vast majority of currently deployed smartphones, which may put people's speech privacy at risk during phone calls. We also propose a practical and effective defense solution. We validate that it is feasible to prevent audio eavesdropping by using random variation of sampling rate.

Diagnostic method and device for evaluating and forecasting the technical condition of farm machinery in operation

The paper discusses methods and ways to diagnose the technical condition of agricultural machines and harvesters, existing practices, and approaches to get reliable data on the current health of the machinery used. The device for assessing and predicting machines’ technical condition includes software and technical means developed with virtual technologies to measure diagnostic parameters of the machinery. The main device elements are digital sensors with physical modifiers (pressure, temperature, medium composition and motion sensors, a-d converters with signal amplifiers), software to configure data gathering, and output to conduct analyses and produce recommendations. The core of the present approach is the technology of virtual prediction of breakdowns by changes in the technical condition parameters. It is based on modular devices, software with an interface that collects and processes data and provides a complete set of failure diagnostics and forecasting. The given method based on a device operating in the information and communication network increases farm machinery’s performance. Furthermore, it reduces operating costs due to the prevention of expensive breakdowns, individual forecasting, and scheduled maintenance of machines in operation. The approach under consideration was applied in the laboratory of digital engineering technologies of the Bashkir State Agrarian University Republic of Bashkortostan of the Russian Federation. The given work is aimed to boost the efficiency of the farm machinery diagnostics and maintenance system by applying a virtual breakdown prediction technology to conduct an automated evaluation, registration, and analysis of a machine’s condition. It can be achieved by developing software and technical means to register data and their structure systematization.

ОСВІТЛЕННЯ ВХІДНОЇ ГРУПИ З ЕЛЕМЕНТОМ РЕЖИМУ ОЧІКУВАННЯ ДЛЯ ЗАКЛАДІВ ЦІЛОДОБОВОЇ РОБОТИ

The main purpose of the study is to create energy-efficient solutions when designing the lighting of the entrance group for the case when the object must provide round-the-clock operation Methodology. To achieve this goal, a method for multi-level connection of light sources of different intensities has been developed. The control of the processes of level regulation is carried out using motion sensors. Results. The modern level of LED products makes it possible to use LED lighting sources as universal ones, allowing you to implement any design solution. The introduction of motion sensors as elements for regulating the intensity of light allows to obtain more than 50% energy savings. Interesting design solutions help create light accents without creating too much lighting on certain objects. Scientific novelty. The work combines multilevel lighting systems using motion sensors as switches operating at night. The authors proposed a sequence of connecting the levels of the system to create the most comfortable stay and a good first impression of the institution. Such a system makes it possible to use lighting not only for practical purposes, but also for the most attractive visual appearance. Practical significance. The versatility of this methodology allows it to be applied to objects of various purposes, including round-the-clock service. However, it is important to plan for such a lighting system even at the design stage of the building in order to obtain the maximum economic benefit.

Removal of the Cervical Spine Collar from Alpine Extrication and Evacuation Skiing Rescue Spinal Motion Restriction Protocols: A Biomechanical Controlled Study in Real-Life Mountain Conditions with a High-Fidelity Mannequin

Background: Alpine skiing rescues are unique because of the mountainous environment and risks of cervical spine motion (CSM) induced during victims’ extrication (EX) and downhill evacuation (DE). Current pre-hospital guidelines recommend the application of full spinal immobilization using various orthotic devices such as cervical collars (CC) when mobilizing and transfer+ring a victim with a suspected spine injury. The biomechanical benefits of applying CC in terms of spinal motion restriction during simulated alpine rescue are undocumented. Methods: Observational design of CSM measurement on a high-fidelity simulation mannequin with a motion sensors-instrumented cervical spine during simulated alpine skiing EX and DE. A total of 32 EXs and 4 DEs on different slope conditions were performed by six experienced active ski patrollers at a Canadian ski resort. The primary outcome was the 3D excursion vector (PeakΔθ) of the mannequin’s head. The secondary objectives were the time to extrication completion (tEX) depending on CC use and to identify which EX event is more likely to induce CSM. Results: PeakΔθ recorded during flat terrain EX using CC was 11.71° +/- 3.61° compared to 16.00° +/- 7.93° using MILS, and 18.29° +/- 9.78° for CC versus 17.90° +/- 4.16° using MILS on a steep slope. PeakΔθ with CC or using MILS during EXs were equivalent according to a 10 degrees non-inferiority hypothesis testing. Time to extrication completion (tEX) was significantly higher using CC as opposed to MILS for both flat and steep terrain conditions (100.6s vs. 219.2s and 106.2s vs. 268.8s longer respectively, 95% confidence interval). During DEs, CSM with and without CC across all terrain conditions were negligible (<5°). Task analysis during EX showed that when CC is used, its installation induces the highest CSM. When EXs are done using MILS without CC, the logroll initiation is the manipulation inducing the highest risk of CSM. Conclusion: For experienced ski patrollers, the biomechanical benefits of motion restriction provided by CC over MILS during alpine skiing rescues were found to be at best marginal and CC use negatively affected rescue time. Systematic use of CC during alpine rescue should be reconsidered.