Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A Low-Resolution Infrared Array for Unobtrusive Human Activity Recognition That Preserves Privacy.

ABSTRACT: This research uses a low-resolution infrared array sensor to address real-time human activity recognition while prioritizing the preservation of privacy. The proposed system captures thermal pixels that are represented as a human silhouette. With camera and image processing, it is easy to detect human activity, but that reduces privacy. This work proposes a novel human activity recognition system that uses interpolation and mathematical measures that are unobtrusive and do not involve machine learning. The proposed method directly and efficiently recognizes multiple human states in a real-time environment. This work also demonstrates the accuracy of the outcomes for various scenarios using traditional ML approaches. This low-resolution IR array sensor is effective and would be useful for activity recognition in homes and healthcare centers.

SUBMITTER: Newaz NT

PROVIDER: S-EPMC10857048 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

A Low-Resolution Infrared Array for Unobtrusive Human Activity Recognition That Preserves Privacy.

Newaz Nishat Tasnim NT Hanada Eisuke E

Sensors (Basel, Switzerland) 20240131 3

This research uses a low-resolution infrared array sensor to address real-time human activity recognition while prioritizing the preservation of privacy. The proposed system captures thermal pixels that are represented as a human silhouette. With camera and image processing, it is easy to detect human activity, but that reduces privacy. This work proposes a novel human activity recognition system that uses interpolation and mathematical measures that are unobtrusive and do not involve machine le ...[more]

PMID: 38339643

Similar Datasets

Human Activity Recognition for AI-Enabled Healthcare Using Low-Resolution Infrared Sensor Data.

Project description:This paper explores the feasibility of using low-resolution infrared (LRIR) image streams for human activity recognition (HAR) with potential application in e-healthcare. Two datasets based on synchronized multichannel LRIR sensors systems are considered for a comprehensive study about optimal data acquisition. A novel noise reduction technique is proposed for alleviating the effects of horizontal and vertical periodic noise in the 2D spatiotemporal activity profiles created by vectorizing and concatenating the LRIR frames. Two main analysis strategies are explored for HAR, including (1) manual feature extraction using texture-based and orthogonal-transformation-based techniques, followed by classification using support vector machine (SVM), random forest (RF), k-nearest neighbor (k-NN), and logistic regression (LR), and (2) deep neural network (DNN) strategy based on a convolutional long short-term memory (LSTM). The proposed periodic noise reduction technique showcases an increase of up to 14.15% using different models. In addition, for the first time, the optimum number of sensors, sensor layout, and distance to subjects are studied, indicating the optimum results based on a single side sensor at a close distance. Reasonable accuracies are achieved in the case of sensor displacement and robustness in detection of multiple subjects. Furthermore, the models show suitability for data collected in different environments.

| S-EPMC9824082 | biostudies-literature

Transparent organic upconversion devices displaying high-resolution, single-pixel, low-power infrared images perceived by human vision.

Project description:Crystalline photodiodes remain the most viable infrared sensing technology of choice, yet the opacity and the limitation in pixel size reduction per se restrict their development for supporting high-resolution in situ infrared images. In this work, we propose an all-organic non-fullerene-based upconversion device that brings invisible infrared signal into human vision via exciplex cohost light-emissive system. The device reaches an infrared-to-visible upconversion efficiency of 12.56% by resolving the 940-nm infrared signal (power density of 103.8 μW cm-2). We tailor a semitransparent (AVT, ~60%), large-area (10.35 cm2), lightweight (22.91 g), single-pixel upconversion panel to visualize the infrared power density down to 0.75 μW cm2, inferring a bias-switching linear dynamic range approaching 80 dB. We also demonstrate the possibility of visualizing low-intensity infrared signals from the Face ID and LiDAR, which should fill the gap in the existing technology based on pixelated complementary metal-oxide semiconductors with optical lenses.

| S-EPMC10132748 | biostudies-literature

IMU-based human activity recognition and payload classification for low-back exoskeletons.

Project description:Nowadays, work-related musculoskeletal disorders have a drastic impact on a large part of the world population. In particular, low-back pain counts as the leading cause of absence from work in the industrial sector. Robotic exoskeletons have great potential to improve industrial workers' health and life quality. Nonetheless, current solutions are often limited by sub-optimal control systems. Due to the dynamic environment in which they are used, failure to adapt to the wearer and the task may be limiting exoskeleton adoption in occupational scenarios. In this scope, we present a deep-learning-based approach exploiting inertial sensors to provide industrial exoskeletons with human activity recognition and adaptive payload compensation. Inertial measurement units are easily wearable or embeddable in any industrial exoskeleton. We exploited Long-Short Term Memory networks both to perform human activity recognition and to classify the weight of lifted objects up to 15 kg. We found a median F1 score of [Formula: see text] (activity recognition) and [Formula: see text] (payload estimation) with subject-specific models trained and tested on 12 (6M-6F) young healthy volunteers. We also succeeded in evaluating the applicability of this approach with an in-lab real-time test in a simulated target scenario. These high-level algorithms may be useful to fully exploit the potential of powered exoskeletons to achieve symbiotic human-robot interaction.

| S-EPMC9867770 | biostudies-literature

Application of a low cost array-based technique - TAB-Array - for quantifying and mapping both 5mC and 5hmC at single base resolution in human pluripotent stem cells.

Project description:5-hydroxymethylcytosine (5hmC), an oxidized derivative of 5-methylcytosine (5mC), has been implicated as an important epigenetic regulator of mammalian development. Current procedures use DNA sequencing methods to discriminate 5hmC from 5mC, limiting their accessibility to the scientific community. Here we report a method that combines TET-assisted bisulfite conversion with Illumina 450K DNA methylation arrays for a low-cost high-throughput approach that distinguishes 5hmC and 5mC signals at base resolution. Implementing this approach, termed "TAB-array", we assessed DNA methylation dynamics in the differentiation of human pluripotent stem cells into cardiovascular progenitors and neural precursor cells. With the ability to discriminate 5mC and 5hmC, we identified a large number of novel dynamically methylated genomic regions that are implicated in the development of these lineages. The increased resolution and accuracy afforded by this approach provides a powerful means to investigate the distinct contributions of 5mC and 5hmC in human development and disease.

| S-EPMC4342188 | biostudies-literature

Unobtrusive assessment of activity patterns associated with mild cognitive impairment.

Project description:Timely detection of early cognitive impairment is difficult. Measures taken in the clinic reflect a single snapshot of performance that might be confounded by the increased variability typical in aging and disease. We evaluated the use of continuous, long-term, and unobtrusive in-home monitoring to assess neurologic function in healthy and cognitively impaired elders.Fourteen older adults 65 years and older living independently in the community were monitored in their homes by using an unobtrusive sensor system. Measures of walking speed and amount of activity in the home were obtained. Wavelet analysis was used to examine variance in activity at multiple time scales.More than 108,000 person-hours of continuous activity data were collected during periods as long as 418 days (mean, 315 +/- 82 days). The coefficient of variation in the median walking speed was twice as high in the mild cognitive impairment (MCI) group (0.147 +/- 0.074) as compared with the healthy group (0.079 +/- 0.027; t(11) = 2.266, P < .03). Furthermore, the 24-hour wavelet variance was greater in the MCI group (MCI, 4.07 +/- 0.14; healthy elderly, 3.79 +/- 0.23; F = 7.58, P </= .008), indicating that the day-to-day pattern of activity of subjects in the MCI group was more variable than that of the cognitively healthy controls.The results not only demonstrate the feasibility of these methods but also suggest clear potential advantages to this new methodology. This approach might provide an improved means of detecting the earliest transition to MCI compared with conventional episodic testing in a clinic environment.

| S-EPMC2664300 | biostudies-literature

A hybrid cloud read aligner based on MinHash and kmer voting that preserves privacy.

Project description:Low-cost clouds can alleviate the compute and storage burden of the genome sequencing data explosion. However, moving personal genome data analysis to the cloud can raise serious privacy concerns. Here, we devise a method named Balaur, a privacy preserving read mapper for hybrid clouds based on locality sensitive hashing and kmer voting. Balaur can securely outsource a substantial fraction of the computation to the public cloud, while being highly competitive in accuracy and speed with non-private state-of-the-art read aligners on short read data. We also show that the method is significantly faster than the state of the art in long read mapping. Therefore, Balaur can enable institutions handling massive genomic data sets to shift part of their analysis to the cloud without sacrificing accuracy or exposing sensitive information to an untrusted third party.

| S-EPMC5440850 | biostudies-literature

Unobtrusive Monitoring the Daily Activity Routine of Elderly People Living Alone, with Low-Cost Binary Sensors.

Project description:Most expert projections indicate that in 2030, there will be over one billion people aged 60 or over. The vast majority of them prefer to spend their last years at home, and almost a third of them live alone. This creates a growing need for technology-based solutions capable of helping older people to live independently in their places. Despite the wealth of solutions proposed for this general problem, there are very few support systems that can be reproduced on a larger scale. In this study, we propose a method to monitor the activity of the elderly living alone and detect deviations from the previous activity patterns based on the idea that the residential living environment can be modeled as a collection of behaviorally significant places located arbitrarily in a generic space. Then we use virtual pheromones-a concept defined in our previous work-to create images of the pheromone distribution maps, which describe the spatiotemporal evolution of the interactions between the user and the environment. We propose a method to detect deviations from the activity routines based on a simple statistical analysis of the resulting images. By applying this method on two public activity recognition datasets, we found that the system is capable of detecting both singular deviations and slow-deviating trends from the previous activity routine of the monitored persons.

| S-EPMC6567306 | biostudies-other

Array-based Identification of Copy Number Changes in a Diagnostic Setting: Simultaneous gene-focused and low resolution whole human genome analysis.

Project description:OBJECTIVES:The aim of this study was to develop and validate a comparative genomic hybridisation (CGH) array that would allow simultaneous targeted analysis of a panel of disease genes and low resolution whole genome analysis. METHODS:A bespoke Roche NimbleGen 12x135K CGH array (Roche NimbleGen Inc., Madison, Wisconsin, USA) was designed to interrogate the coding regions of 66 genes of interest, with additional widely-spaced backbone probes providing coverage across the whole genome. We analysed genomic deoxyribonucleic acid (DNA) from 20 patients with a range of previously characterised copy number changes and from 8 patients who had not previously undergone any form of dosage analysis. RESULTS:The custom-designed Roche NimbleGen CGH array was able to detect known copy number changes in all 20 patients. A molecular diagnosis was also made for one of the additional 4 patients with a clinical diagnosis that had not been confirmed by sequence analysis, and carrier testing for familial copy number variants was successfully completed for the remaining four patients. CONCLUSION:The custom-designed CGH array described here is ideally suited for use in a small diagnostic laboratory. The method is robust, accurate, and cost-effective, and offers an ideal alternative to more conventional targeted assays such as multiplex ligation-dependent probe amplification.

| S-EPMC3616803 | biostudies-literature

Am I who I say I am? Unobtrusive self-representation and personality recognition on Facebook.

Project description:Across social media platforms users (sub)consciously represent themselves in a way which is appropriate for their intended audience. This has unknown impacts on studies with unobtrusive designs based on digital (social) platforms, and studies of contemporary social phenomena in online settings. A lack of appropriate methods to identify, control for, and mitigate the effects of self-representation, the propensity to express socially responding characteristics or self-censorship in digital settings, hinders the ability of researchers to confidently interpret and generalize their findings. This article proposes applying boosted regression modelling to fill this research gap. A case study of paid Amazon Mechanical Turk workers (n = 509) is presented where workers completed psychometric surveys and provided anonymized access to their Facebook timelines. Our research finds indicators of self-representation on Facebook, facilitating suggestions for its mitigation. We validate the use of LIWC for Facebook personality studies, as well as find discrepancies with extant literature about the use of LIWC-only approaches in unobtrusive designs. Using survey data and LIWC sentiment categories as predictors, the boosted regression model classified the Five Factor personality model with an average accuracy of 74.6%. The contribution of this work is an accurate prediction of psychometric information based on short, informal text.

| S-EPMC5604947 | biostudies-literature

Low-dose irradiation of mouse embryos increases Smad-p21 pathway activity and preserves pluripotency.

Project description:PurposeTo study the outcomes of mouse preimplantation embryos irradiated with low doses of X-rays (≤ 1 Gy) and investigate apoptosis and pluripotency of the irradiated embryos.MethodsMouse embryos at the 2-cell stage were collected for in vitro culture. After reaching the 8-cell stage, embryos were irradiated with various low doses of X-rays (0-1 Gy). Blastocysts with a normal appearance were transferred into a pseudopregnant uterus. The developmental rate to blastocysts and the survival rate following embryo transfer were examined. Expression levels of p21, Smad2, Foxo1, Cdx2, Oct4, and Nanog genes were measured by RT-PCR. Apoptotic cells in mouse blastocysts were examined immunofluorescently by staining for cleaved caspase-3.ResultsMore than 90% of non-irradiated and low-dose X-ray-irradiated preimplantation embryos developed to morphologically normal blastocysts that could be implanted and survive in the uterus. However, embryos irradiated with X-rays had more apoptotic cells in a dose-dependent manner. Expression of p21, Smad2, and Foxo1 genes in X-ray-irradiated embryos was increased significantly, while expression of Cdx2, Oct4, and Nanog genes was maintained in comparison with non-irradiated embryos.ConclusionsAlthough irradiated embryos contained apoptotic cells, the low doses of irradiation did not disturb development of 8-cell stage embryos to blastocysts or their survival in utero. The underlying mechanisms might involve anti-apoptotic systems, including the Smad-p21 pathway, and preservation of pluripotency.

| S-EPMC6030001 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data