Human Activity Monitoring Research Articles

Nighttime light extent and intensity explain the dynamics of human activity in coastal zones

Studying human activity in coastal areas is crucial for urban planning, sustainability, and economic development. However, there is limited evidence of ongoing monitoring of human activities in these areas. Thus, a quantitative analysis of the spatio-temporal changes, trends, and variability of Nighttime light (NTL) in the Italian Coastal Zone over the past decade (2014–2023) was conducted to assess human activity dynamics. The findings of our study indicate the following: (1) NTL increases over the years in both extent and intensity along the coastal zone; (2) NTL extent and intensity vary by season, with the coastal zone being brighter in summer; and (3) a highly heterogeneous NTL pattern was found where some locations became hot spots (significant upward trend) or cold spots (significant downward trend) while others remain unchanged. By explaining the intensification of human activity, this study can provide insight into identifying the patterns of economic development and environmental conditions contributing to more effective planning in coastal zones.

Space observation for the sustainable utilization of world heritage sites along the silk roads: the routes network of Chang’an-Tianshan corridor

ABSTRACT Urban development under a changing climate pose threats to heritage conservation, necessitating vigilant monitoring of human activities and natural disasters. This study proposes a dynamic monitoring and risk assessment technology aimed at identifying interferences to heritage sites along the Silk Road. The characterization of land use was investigated, and changes within the protected areas were extracted using an object-based deep learning method to reveal instances of human interference. Nighttime light changes were analyzed to assess socio-economic development in heritage regions and cross-referenced with results indicating human interference to examine the relationship between urban development and heritage conservation. Additionally, we extracted various environmental and climate variables to evaluate the risk of flood disasters for these heritage sites. The findings suggest that heritage sites along the Silk Road are generally in good condition. Nevertheless, the substantial increase in construction land highlights challenges in heritage conservation and economic development. This study highlights the importance of vegetation coverage and water diversion measures to prevent floods, emphasizing the effectiveness of space observation in identifying risks. Such observation can help the government manage and protect valuable sites, advancing heritage protection within the framework of sustainable development goals (SDGs).

A global annual simulated VIIRS nighttime light dataset from 1992 to 2023

Nighttime light (NTL) data is recognized as a reliable proxy for measuring the scope and intensity of human activity, finding wide application in studies such as urbanization monitoring, socioeconomic estimation, and ecological environment assessment. However, the substantial discrepancies and limited temporal coverage of existing NTL datasets have constrained their potential for long-term research applications. To address this, a Nighttime Light U-Net super-resolution network is proposed for the cross-sensor calibration between the Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) NTL data and the Suomi National Polar-Orbiting Partnership-Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) NTL data. This network is applied to generate a continuous and consistent 500-meter global annual simulated VIIRS NTL dataset (SVNL) from 1992 to 2023. Validation results indicate a high confidence in the quality of the SVNL data, demonstrating its superiority in capturing longer NTL dynamics, maintaining higher temporal consistency, and presenting greater spatial detail compared with other NTL datasets. The SVNL could be utilized for prolonged human activities monitoring, and further research on regional or global urbanization.

Highly Sensitive Multidirectional Strain Sensors Based on Laser-Induced Graphene for Human Activity Monitoring

Highly Sensitive Multidirectional Strain Sensors Based on Laser-Induced Graphene for Human Activity Monitoring

Machine learning enabled smart human activity monitoring using corn husk based eco-friendly triboelectric nanogenerator

ABSTRACT The keys to success in health status clinical investigations, fitness services, and several other related fields are accurate identification of human actions. In this study, the machine learning is integrated with corn husk based biodegradable and environment friendly triboelectric nanogenerator (TENG). This self-powered sensor designed and fabricated in this present study is used for smart human activity monitoring. We devote our focus on using biodegradable materials to make environmentally friendly devices as a green energy source. The corn husk used in this study is a natural agriculture waste by-product. This corn husk based sensor is capable of generating 140 volts and charging various commercial capacitors. This eco-friendly sensing device is also tested as a wearable sensor to gather data and track the user’s physical activity, such as jumping, running, and walking. For accurate prediction of human activity, the designed corn husk based sensor is coupled with an extra randomized tree and random forest-based machine learning model. These models achieve a 98.89% and 98.33% accuracy rate in identifying the user’s three activities. The research presents a novel strategy to support tailored applications of TENG sensors in human motion tracking and enables the development of intelligent, self-sufficient systems for novel uses.

Highly stretchable, self-healing, adhesive, 3D-printable and antibacterial double-network hydrogels for multifunctional wearable sensors.

Conductive hydrogels based on sodium alginate (SA) have potential applications in human activity monitoring and personal medical diagnosis due to their good conductivity and flexibility. However, most sensing SA-hydrogels exhibit poor mechanical properties and lack of self-healing, self-adhesive, and antibacterial properties, greatly limiting their practical applications. Therefore, in this paper, a multifunctional double-network PAA-SA hydrogel consisting of poly(acrylic acid) (PAA) and sodium alginate (SA) was prepared by a simple strategy. As a rigid network structure, SA endowed the hydrogel double network structure with excellent mechanical performance. As a wearable sensor, the PAA-SA hydrogel exhibited excellent tensile properties (strain: 1799.2 %), self-healing, high sensitivity (GF = 9.9), reliable repeatability, self-adhesive, 3D printability and antibacterial activity. Additionally, the highly sensitive wearing sensing PAA-SA hydrogel could accurately and real-time monitor various intense or subtle human movements, such as joint bending, face and throat vibration. Moreover, PAA-SA hydrogels were not only used for handwritten recognition of Arabic numerals and English letters, but also for real-time sensing of temperature changes and monitoring of human sweating. The prepared multifunctional wearable sensing hydrogel has the advantages of simple and versatile methods and low cost, making it a promising candidate for applications in different fields such as electronic skin, soft robotics, and medical monitoring.

A versatile optoelectronic device for ultrasensitive negative-positive pressure sensing applications

In the work, a versatile optoelectronic device with ultrasensitive negative-positive pressure sensing capabilities, integrated with a wireless monitoring system is fabricated and demonstrated. The device comprises a monolithic GaN chip with a polydimethylsiloxane cavity and nanograting, which effectively transduces pressure stimuli into optical changes detected by the GaN chip. The developed device exhibits an ultra-low detection limit for a mass of 0.03 mg, a pressure of 2.94 Pa, and a water depth of 0.3 mm, with a detection range of -100 kPa to 30.5 kPa and high stability. The versatility of the device is demonstrated by its ability to monitor heart pulse, grip strength, and respiration. Its integration with a wireless data transmission system enables real-time monitoring of human activity and heart rate underwater, making it suitable for precise measurements in various practical applications.

Mussel-Inspired Adhesive and Tough Composite Hydrogel Based on Polydopamine-Modified Nanocellulose for Strain and Wireless Sensing.

Adhesive composite hydrogels have received increasing attention in the fields of wearable sensors, electronic skin, and bioelectronic interfaces. However, combining good adhesiveness and high strength in a single composite hydrogel remains challenging. To address this issue, a polydopamine (PDA)-modified nanocellulose (PCNF)/polyacrylamide (PAM) composite hydrogel was developed, which exhibits good adhesiveness (40 kPa), good durability (1500 rpm), excellent frost resistance (-42 °C), and good sensitivity (GF = 1.6). The composite hydrogel exhibits self-healing and conductive properties, making it suitable for sensing and Morse code applications. The obtained composite hydrogels have potential applications in various wearable devices, wireless human computer interfaces, human activity monitoring, and remote encrypted transmissions.

Non-contact monitoring of human cardiorespiratory activity during sleep using FMCW millimeter wave radar

Millimeter wave radar can be utilized for non-contact, long-term, and accurate health monitoring. This paper presents an application for vital signs detection including respiratory rate (RR) and heart rate (HR) during sleep, as well as facilitating rapid detection and extended recording of apnea syndrome. This paper employs frequency spectrum analysis for RR estimation and develops an algorithm of template matching estimation (TME) for real-time, accurate HR estimation by comparing radar signal fragments to a template with a frequency signature. The time required for HR estimation is reduced to 1 s. In addition, a neural network-based model was developed for detecting the apnea events with the accuracy of 93.60% and calculates the duration in seconds. The system underwent testing using irregular analog signals of vital signs. In the actual scene testing, the accuracy of the RR estimation is 90.58%, and 90.25% for HR estimation.

Multi‐Scenario Applications of Multi‐Dimensional Yarn‐Based Wearable Integrated Sensors

Abstract1D yarn sensors, crucial for smart textiles, face challenges in achieving diverse functionalities, multiple applications, and durability in harsh environments. Herein, a simple strategy is proposed to prepare reduced graphene oxide‐polyimide yarns (rGO‐PYs), constructing functional and multi‐dimensional sensors for multi‐scenario applications. rGO‐PYs can detect multiple mechanical stimuli, and exhibit a broad bending and pressure response range (0°–180° and 0.12–62.39 KPa), quick response and recovery time (both <100 ms), and excellent cyclic stability. It features real‐time monitoring of human activities, such as joint movements, speech, writing, respiratory, pulse, and heart rate. rGO‐PYs exhibit a remarkable resilience to harsh environments, whether in liquid nitrogen (−196 °C), high temperature (300 °C), acid, or base. Crucially, expanded into an integrated 2D fabric, rGO‐PYs maintain their exceptional multi‐dimensional sensing. The point contact pressure sensor (PCPS) and pressure sensing array showed remarkable sensing performance in identifying pressure and its distribution. This work establishes a comprehensive system from preparation to application, encompassing 1D yarns large‐scale fabrication, functional sensing validation, integration into multi‐dimensional sensors, and diverse cross‐scenario applications. The innovative system would transform traditional yarns into intelligent fabrics, further advancing functional yarns into multi‐dimensional sensors (1D to 2D and 3D), enabling their diverse multi‐scenario applications.

Steady-State Visual Evoked Potential-Based Brain-Computer Interface System for Enhanced Human Activity Monitoring and Assessment.

Advances in brain-computer interfaces (BCIs) have enabled direct and functional connections between human brains and computing systems. Recent developments in artificial intelligence have also significantly improved the ability to detect brain activity patterns. In particular, using steady-state visual evoked potentials (SSVEPs) in BCIs has enabled noticeable advances in human activity monitoring and identification. However, the lack of publicly available electroencephalogram (EEG) datasets has limited the development of SSVEP-based BCI systems (SSVEP-BCIs) for human activity monitoring and assisted living. This study aims to provide an open-access multicategory EEG dataset created under the SSVEP-BCI paradigm, with participants performing forward, backward, left, and right movements to simulate directional control commands in a virtual environment developed in Unity. The purpose of these actions is to explore how the brain responds to visual stimuli of control commands. An SSVEP-BCI system is proposed to enable hands-free control of a virtual target in the virtual environment allowing participants to maneuver the virtual target using only their brain activity. This work demonstrates the feasibility of using SSVEP-BCIs in human activity monitoring and assessment. The preliminary experiment results indicate the effectiveness of the developed system with high accuracy, successfully classifying 89.88% of brainwave activity.

In-situ cured gel polymer/ecoflex hierarchical structure-based stretchable and robust TENG for intelligent touch perception and biometric recognition

Gel-based sensors for next generation touch panels have been acknowledged for their exceptional sensitivity and flexibility. However, these sensors typically depend on a metal grid connection, which is susceptible to structural deformation under heavy stress applications and necessitates external power. Here, we report a novel in-situ cured gel polymer electrode-based triboelectric nanogenerator (GPE-TENG) that is stretchable, semi-transparent, and durable, designed to enable a self-powered touch panel for intelligent touch perception. The in-situ curing of the hierarchical structure of the ionic polymer gel encapsulated within the ecoflex ensures robust adhesion of the ionic conductive polymer gel (PEO/LiTFSI) to the ecoflex layers, addressing the issue of delamination in TENG components under mechanical stress. As a result, the GPE-TENG demonstrates high durability, enduring under stretching of approximately 375 % and sustaining heavy mechanical deformations (under folding, twisting, and rolling) over a long period (approximately 2 months) without loss of functionality. Remarkably, the GPE-TENG exhibits outstanding energy harvesting capabilities with a peak power density of 0.36 W m-2. Notably, the GPE-TENG generates electrical signals through simple device stretching, thus serving as a self-powered wearable sensor for human activity monitoring. Moreover, a 9-digital arrayed (3 × 3) flexible, semi-transparent, and self-powered touch panel based on the GPE-TENG shows multifunctionality, including touch track/pattern recognition (i.e. touch and sliding mode) and a highly accurate (∼98 %) deep learning assisted smart biometric system for user identification.

Flexible Piezoelectric 0–3 PZT@C/PDMS Composite Films for Pressure Sensor and Limb Motion Monitoring

The flexible piezoelectric pressure sensor is essential in areas such as machine sensing and human activity monitoring. Here, 0-dimensional PZT piezoelectric ceramic nanoparticles with carbon coating were synthesized by a surface-modified technique. The excellent electrical conductivity of the carbon shell causes redistribution and accumulation of mobile charges in the carbon layer, resulting in a greatly increased piezoelectric effect by inducing an enhanced electric field. A series of organic–inorganic composite films were prepared by the spin-coating method using polydimethylsiloxane (PDMS) as the matrix. The as-fabricated flexible PZT@C/PDMS composite film with 40 wt% PZT@C powder exhibits an excellent output voltage of ~74 V, a peak of output current ~295 nA, as well as a big sensitivity of 5.26 V N−1. Moreover, the composite film can be used as a pressure sensor to detect changes in force as well as for monitoring limb movements such as finger flexion, wrist flexion, and pedaling. This study reveals the promising applications of flexible 40%PZT@C/PDMS composite film for limb motion monitoring and pressure sensing.

A conductive ionogel with Stretchability, low hysteresis and adjustable adhesion for Air/Underwater mechanosensing

Conductive ionogels based on deep eutectic solvents (DESs) have great application potential in the field of flexible sensors. However, the development of conductive ionogels that are stable under various environmental conditions (such as high and low temperatures, air, and water) remains extremely challenging. In this work, the hydrophobic conductive ionogel BxHyIG was prepared via a one-step photoinitiated copolymerization of butyl acrylate and N-hydroxyethylacrylamide in a hydrophobic DES. The good chemical compatibility between the polymer and DES, as well as the dense and reversible ion–dipole interactions, dipole–dipole interactions and hydrogen bond interactions, endow BxHyIG with satisfactory transparency (80 %), adhesion (polystyrene: 74.56 kPa), mechanical properties (elongation at break: 578 %, tensile strength: 171.25 kPa), a low degree of hysteresis (DH=1.9 %) and conductivity (3.95 × 10-3 S m−1). Strain/pressure sensors and bioelectrodes prepared from ionogels have the characteristics of high sensitivity, fast response and excellent stability and can be used for real-time monitoring of human activities and health status in the atmosphere. In addition, the inherent hydrophobicity of BxHyIG (water contact angle > 110°) can effectively prevent BxHyIG from being eroded and swollen by water, thereby achieving reliable underwater sensing. More importantly, by directly exposing BxHyIG to air or storing it in nitrogen, the surface adhesion of conductive ionogels can be effectively regulated to obtain double-sided, single-sided or even nonadhesive ionogels. Therefore, this study provides new ideas for the development of conductive ionogels that can be applied under various environmental conditions.

Visual Pollution of the Banks of the Tigris River in Baghdad City Capital of Iraq

The study titled "Visual Pollution of the Tigris Riverbanks in Baghdad City" consists of two main sections: the first section is dedicated to the theoretical framework, while the second section covers the practical aspect (field study). Specific areas of Baghdad were selected for this study due to the widespread presence of solid waste along the riverbanks. The importance of the study lies in the fact that visual pollution is one of the dangerous types of pollution that affects both human health and the environment. The study concluded that visual pollution along the Tigris River banks results from the impact of human activities spread linearly along the river, and the lack of environmental awareness among residents has negatively affected the river environment through the disposal of household and construction waste and the discharge of untreated wastewater from sewage treatment plants. The research recommends the importance of strict monitoring of human activities near the river, imposing financial penalties on violators of environmental standards, and working on rehabilitating and developing the riverbanks to make them attractive environments for residents, turning them into tourist and recreational areas that serve the city.

Transparent RFID tag wall enabled by artificial intelligence for assisted living

Current approaches to activity-assisted living (AAL) are complex, expensive, and intrusive, which reduces their practicality and end user acceptance. However, emerging technologies such as artificial intelligence and wireless communications offer new opportunities to enhance AAL systems. These improvements could potentially lower healthcare costs and reduce hospitalisations by enabling more effective identification, monitoring, and localisation of hazardous activities, ensuring rapid response to emergencies. In response to these challenges, this paper introduces the TransparentRFIDTag Wall (TRT-Wall), a novel system taht utilises a passive ultra-high frequency (UHF) radio-frequency identification (RFID) tag array combined with deep learning for contactless human activity monitoring. The TRT-Wall is tested on five distinct activities: sitting, standing, walking (in both directions), and no-activity. Experimental results demonstrate that the TRT-Wall distinguishes these activities with an impressive average accuracy of 95.6%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$95.6\\%$$\\end{document} under four distinct distances (2, 2.5, 3.5 and 4.5 m) by capturing the RSSI and phase information. This suggests that our proposed contactless AAL system possesses significant potential to enhance elderly patient-assisted living.

Recent Advances in Wearable Textile-Based Triboelectric Nanogenerators.

We review recent results on textile triboelectric nanogenerators (T-TENGs), which function both as harvesters of mechanical energy and self-powered motion sensors. T-TENGs can be flexible, breathable, and lightweight. With a combination of traditional and novel manufacturing methods, including nanofibers, T-TENGs can deliver promising power output. We review the evolution of T-TENG device structures based on various textile material configurations and fabrication methods, along with demonstrations of self-powered systems. We also provide a detailed analysis of different textile materials and approaches used to enhance output. Additionally, we discuss integration capabilities with supercapacitors and potential applications across various fields such as health monitoring, human activity monitoring, human-machine interaction applications, etc. This review concludes by addressing the challenges and key research questions that remain for developing viable T-TENG technology.

Alkylated MXene-Carbon Nanotube/Microfiber Composite Material with Flexible, Superhydrophobic, and Sensing Properties.

Superhydrophobic strain sensors are highly promising for human motion and health monitoring in wet environments. However, the introduction of superhydrophobicity inevitably alters the mechanical and conductive properties of these sensors, affecting sensing performance and limiting behavior monitoring. Here, we developed an alkylated MXene-carbon nanotube/microfiber composite material (AMNCM) that is simultaneously flexible, superhydrophobic, and senses properties. Comprising a commercially available fabric substrate that is coated with a functional network of alkylated MXene/multi-walled carbon nanotubes and epoxy-silicone oligomers, the AMNCM offers high mechanical and chemical robustness, maintaining high conductivity and strain sensing properties. Furthermore, the AMNCM strain sensor achieves a gauge factor of up to 51.68 within a strain range of 80-100%, and exhibits rapid response times (125 ms) and long-term stability under cyclic stretching, while also displaying superior direct/indirect anti-fouling capabilities. These properties position the AMNCM as a promising candidate for next-generation wearable devices designed for advanced environmental interactions and human activity monitoring.

Hierarchically structured hollow PVDF nanofibers for flexible piezoelectric sensor

The emergence of flexible sensors addresses the limitations of traditional detection equipment, such as large size, high cost, and inconvenient portability. These sensors have significantly advanced the development of wearable electronic devices for applications in electronic skin, energy harvesting, and energy storage. To enhance the sensitivity of flexible sensors, we developed a hierarchical polyvinylidene fluoride (PVDF) nanofiber-based piezoelectric sensor. By utilizing coaxial electrospinning, we fabricated nanofibers with hollow interiors and porous outer walls. Additionally, microstructures were constructed on the fiber membrane surface by modifying the collector’s shape. The resulting microstructured hollow PVDF nanofiber membrane exhibited high β-phase content (91.31 %), excellent flexibility (maximum strain 56.9 %), and high porosity (88.94 %). The sensor demonstrated a sensitivity of 2.7 V/N (1.08 V/kPa) and a maximum output voltage of 10.1 V, approximately three times higher than that of solid PVDF nanofibers without microstructures. Even after 14,400 cycles of impact, the sensor maintained stable output. The sensor was successfully applied to human activity monitoring and gesture recognition, showcasing its ability to monitor various human activities, respond rapidly (60.4 ms), and synchronously control a mechanical palm to perform different gestures. This work highlights the potential of hierarchically structured hollow PVDF nanofibers in advancing the performance and application scope of flexible piezoelectric sensors.

Highly sensitive flexible pressure sensor based on laser ablated Ag-MWCNT /MXene for human motion detection

The complex and dynamic human environment, higher requirements are put forward for the high-performance flexible pressure sensors. The materials selection and microstructure design are crucial to achieve high sensitivity and stability. In this work, we fabricated pressure sensitive layer with multiple dimensional materials. Using laser ablation in liquid method, Ag nanoparticles were uniformly distributed in surface of multi-walled carbon nanotubes (MWCNT). Combined with the delaminated MXene, highly pressure sensitive composite could be prepared due to the reduction of contact resistance under pressure. The corresponding piezoresistive sensors showed high sensitivity (12.7 kPa−1), excellent response speed (150 ms), recovery speed (100 ms), and distinguished cycle stability (3000 cycles). Based on the performance of the sensor, it can realize the monitoring of tiny pressure on the human body, and further realize the detection of human activities and health. In addition, the sensor array has spatial recognition capability, providing a way of thinking for the development needs of future intelligent wearable electronic devices. The sensors can measure changes in resistance caused by finger bending, slight breathing, pulse, vocal cord vibration, and other movements to realize human activity and health monitoring. At the same time, the 3×3 sensor array system can recognize the layout of pressure in space. This simple preparation and low cost of the sensor can Facilitate the progress towards sophisticated wearable electronic gadgets.