Life Technologies Research Articles

Examining the Digital Technology Usage of Older Adults as Determinants of Life Satisfaction in the Digital Divide.

The digital divide has become a growing source of inequality, as older adults face challenges in adopting and using digital technologies in daily life. Few studies have explored how different types of digital technology usage in various life domains among older adults impact their overall well-being. This study addresses this gap by suggesting effective directions for reducing the cross-generational digital divide. To this end, it analyzed de-identified secondary data from 864 South Korean adults above 65years, surveyed by the National Information Society Agency (NIA). The findings show that digital efficacy positively affects older adults' life satisfaction, mediated by their perceptions of digital technology. Additionally, social networking through digital technology positively influences their life satisfaction through the same mediation. Our findings suggest that policymakers should prioritize the development of educational programs to improve digital efficacy and social networking, which will ultimately enhance older adults' well-being.

Analisis Perbandingan Laba UMKM Sebelum dan Sesudah Menggunakan QRIS (Studi Kasus Pada: UMKM Kuliner Bandar Lampung)

The very rapid development of technology can be seen from the large number of people who use technology in everyday life. The presence of non-cash payments such as QRIS can increase efficiency in managing the finances of a business but can also increase the profits of a business. The use of QRIS is increasingly being used by MSMEs, there are various promotions carried out, as well as various other factors that can influence the success of MSMEs because it increases efficiency (ease) in transactions and makes it easier for MSMEs to carry out buying and selling transactions and book keeping their finances. This research aims to determine the comparison of MSME profits before and after using QRIS in Bandar Lampung Culinary MSMEs, so it is classified as associative or relationship research, namely research to determine cause and effect, using quantitative research methods. The data in this research was obtained using a questionnaire distributed to 30 culinary MSMEs using QRIS in Bandar Lampung City. To analyze the data, the SPSS application was used. The results of this research showed that there were differences in MSME profits before and after using QRIS in Bandar Lampung Culinary MSMEs. This was concluded based on the independent t test. It can be seen that the significance value is smaller than 0.05 (0.001 0.05). In this research, the significance value is smaller than the stipulated significance value, namely 0.05, so we accept the hypothesis, namely that there is a difference in MSME profits before and after using QRIS in Bandar Lampung Culinary MSMEs.

Implementation of Control Valves System on Microturbine Drone’s Rotational Motion

The drone technology has received a wide range of research focusing on improving flight dynamics, battery life, payload capacity and sensor technology. However, for the applications of using drone for high rise buildings are limited by battery life for longer flight with longer duration tasks. This work presents the implementation of a control valve systems for the rotational motion of a microturbine drone. The first objective of this project was to design and develop a control valve system for a microturbine with propeller. The second objective was to measure micro turbine’s performance output which consisted of revolution per minute (rpm) and voltage (V) produced with the control valves system. The final objective was to verify the effectiveness of the control valve system by measuring the differences of the turbine speed of each turbine on the quadcopter to conceptually control the rotational motion of the drones. In conclusion, this work demonstrated the concept of the developed control valve system that can control the rotational motion of the drone.

Poly(vinyl alcohol)/tannic acid nanofibrous membrane containing curcumin as an intelligent indicator of food spoilage

In recent years, active packaging technology for extending food shelf life and intelligent packaging technology for monitoring food freshness have become essential for ensuring food safety. Among sensing technologies, pH-sensitive sensors have notable advantages, including simplicity, compactness, and affordability, making them ideal for monitoring food freshness. This study proposes an intelligent food indicator based on a composite nanofiber membrane fabricated by electrospinning. The membrane, composed of poly(vinyl alcohol) (PVA), tannic acid (TA), and the natural pH-sensitive dye curcumin (CUR), was heat-treated to enhance its moisture stability for food packaging. Furthermore, the incorporation of TA and CUR into PVA provides additional benefits such as UV-blocking, antioxidant, and antimicrobial properties, effectively delaying food spoilage. The CUR-incorporated nanofibrous membrane exhibited faster detection of shrimp spoilage via colorimetric changes under increasingly alkaline conditions than film samples. Moreover, compared to film-based samples, the composite nanofiber membrane exhibited faster color change responsiveness owing to its porous and high surface area structure, thus serving as an efficient and intelligent indicator.

Analisis Strategi Pembelajaran Sains Berbasis Salingtemas dalam Membangun Sikap Ilmiah Siswa

The advancement of science will boost technology, technological advancement will bring negative and positive impacts in life, so that students have concern, awareness, scientific attitude and are responsible for their environment, so quality science learning is needed to prevent environmental damage. This study aims to describe science learning with salingtemas to build students' scientific attitudes. The method used in this study is the Systematic Literature Review method, which is a research method to identify, study, evaluate, and interpret data systematically through searching for journal articles from the Google Scholar and Publish or Perish 8 databases published from 2018 to 2024 from the journal search 208 articles were obtained, after being filtered into 34 articles, then selected using the keywords "salingtemas" and "science learning approach" a study of 27 articles was obtained then adjusted again to the specific needs of the research article and obtained 9 articles, this will then be analyzed. The results of the study show that science learning with a mutual-theme approach can improve scientific attitudes, critical thinking, creativity, discipline, sensitivity, objectivity, care, cooperation, and responsibility towards oneself and protecting the environment from the negative impacts of the use of technology in life.

A Pilot Randomized Controlled Study to Determine the Effect of Real-Time Videos With Smart Glass on the Performance of the Cardiopulmonary Resuscitation.

The aim of this study was to determine the effect of real-time videos with smart glasses on the performance of cardiopulmonary resuscitation performed by nursing students. In this randomized controlled pilot study, the students were randomly assigned to the smart glass group (n = 12) or control group (n = 8). Each student's cardiopulmonary resuscitation performance was evaluated by determining sequential steps in the American Heart Association algorithm they applied and the accuracy and time of each step. A higher number of participants correctly checked response breathing, requested a defibrillator, activated the emergency response team, and provided appropriate chest compressions and breaths in the smart glass group than the control group. There were significant differences between groups. Furthermore, more participants significantly corrected chest compression rate and depth and hand location, used a defibrillator, and sustained cardiopulmonary resuscitation until the emergency response team arrived in the smart glass group than in the control group. Additionally, a significantly shorter time was observed in the smart glass group than in the control group in all variables except time to activate the emergency response team (P < .05). Remote expert assistance with smart glass technology during cardiopulmonary resuscitation is promising. Smart glass led to a significantly better ABC (airway, breathing, circulation) approach, chest compression depth and rate, and hand position. Furthermore, remote expert assistance with smart glass has the potential to improve overall resuscitation performance because it enabled students to initiate resuscitation, use a defibrillator, and defibrillate patients earlier. Nurses may benefit from smart glass technology in real life to provide effective cardiopulmonary resuscitation.

First report of lily mottle virus naturally infecting lily (Lilium asiatica) in Texas, USA.

Lily (Lilium asiatica) is an important plant grown for its range of flower colors and heavy scent. In March 2024, potyvirus-like symptoms consisting of light-yellow mottling and mosaic were noticed on 12/20 lily plants in a private property in Weslaco, Hidalgo County, Texas. Two symptomatic plants (WTX1 and WTX2) were sampled randomly for virus diagnosis. The leaf extracts of both samples were negative for the potyvirus group using Agdia's Poty ImmunoStrip® (Agdia, Inc., Elkhart, IN, USA). However, rub-inoculation of the extracts onto healthy Nicotiana benthamiana and Vigna unguiculata plants (n=4, each) induced mild mottle symptoms on the systemic leaves of both herbaceous test plants 20 to 28 days post inoculation, indicating the presence of a mechanically transmissible agent in the samples. No virus-like symptoms were observed on the mock-inoculated plants (n=1, each) of both species. To test for suspected potyvirus infection, 2-µg of total nucleic acid extracts (Dellaporta et al. 1983) from WTX1 and WTX2 were used for complimentary DNA (cDNA) synthesis with Oligo(dT) primer and the PrimeScript 1st strand cDNA synthesis kit (Takara Bio, USA). One microliter aliquot of each cDNA served as template in 12.5-µl conventional PCR reaction volumes with 5 U Taq polymerase (Roche Diagnostics, Indianapolis, IN), and two pairs of degenerate primers targeting the partial cylindrical inclusion (CI) gene and the helper component protease (HC-Pro) of potyviruses (Ha et al. 2008). The expected ~700-bp DNA product of each gene target was amplified from both samples. The amplicons were excised, gel eluted (Zymoclean™ Gel DNA Recovery kit) and cloned individually into the pJET1.2/Blunt vector (Life Technologies). Recombinant plasmids from two transformed Escherichia coli cells per cloned DNA insert were Sanger sequenced. BLASTn analysis of each gene-specific nucleotide (nt) sequence fragment revealed their identities (83 to 92 % nt) as lily mottle virus (LMoV; genus Potyvirus) at 93 to 98% query coverage. In pairwise comparison, the obtained sequences of LMoV isolates from TX specific to the CI (GenBank accession nos. PQ037260-61) and the HC-Pro (PQ037262-63) shared ~99% nt and 100% amino acid (aa) identities with each other and ~91-92% nt and 98-100% aa identities with the closest isolate, Bate5 (JN127341) from Australia. Based on these results, a pair of LMoV-specific primers (LM_v109-F: 5'-GGCCAGTAATGTGCACAAGC-3' and LM_c527-R: 5'-TCGCTGTAGCTAGCGACGTAC-3') was newly designed to target the partial CI gene, internal to the 700-bp fragment obtained above with the generic primers. The primer pair was used to screen each of the mechanically inoculated test plants by RT-PCR as previously described above. The expected 438-bp fragment of the LMoV CI gene was amplified from all the inoculated plants of both N. benthamiana and V. unguiculata; the results were confirmed by Sanger sequencing as described above. The mock-inoculated plant of each experimental host plant tested negative for LMoV. LMoV is a quarantine pest and was previously reported in the U.S. (Brierley and Smith, 1944) and other lily-producing parts of the world, such as the Netherlands, China, Korea, and Brazil. To our knowledge, this is the first confirmed report of the virus in Texas, thus expanding its geographical range. Testing of lily foundation stocks before propagation is essential to prevent further spread of LMoV via planting material.

Ab initio characterization of protein molecular dynamics with AI2BMD.

Biomolecular dynamics simulation is a fundamental technology for life sciences research, and its usefulness depends on its accuracy and efficiency1-3. Classical molecular dynamics simulation is fast but lacks chemical accuracy4,5. Quantum chemistry methods such as density functional theory can reach chemical accuracy but cannot scale to support large biomolecules6. Here we introduce an artificial intelligence-based ab initio biomolecular dynamics system (AI2BMD) that can efficiently simulate full-atom large biomolecules with ab initio accuracy. AI2BMD uses a protein fragmentation scheme and a machine learning force field7 to achieve generalizable ab initio accuracy for energy and force calculations for various proteins comprising more than 10,000 atoms. Compared to density functional theory, it reduces the computational time by several orders of magnitude. With several hundred nanoseconds of dynamics simulations, AI2BMD demonstrated its ability to efficiently explore the conformational space of peptides and proteins, deriving accurate 3J couplings that match nuclear magnetic resonance experiments, and showing protein folding and unfolding processes. Furthermore, AI2BMD enables precise free-energy calculations for protein folding, and the estimated thermodynamic properties are well aligned with experiments. AI2BMD could potentially complement wet-lab experiments, detect the dynamic processes of bioactivities and enable biomedical research that is impossible to conduct at present.

Improved machine learning models with a similarity-based approach for remaining useful life prediction

Abstract Cost efficiency is a critical factor in the competitive aviation sector. These efficiency factors force airline operators to develop new approaches in their organizations. Predictive maintenance helps to build scheduling maintenance programs for airline operators or MROs. Scheduled maintenance programs benefit cost efficiency in the aviation sector. Predictive maintenance methods predict the failure time of any equipment. Predictions can be made by analyzing the sensor values from equipment. In this paper, we predicted the remaining useful life (RUL) of turbofan engines using machine learning models and a similarity-based approach. Sensor datasets from the Prognostics Data Repository of NASA, called CMAPPS, were utilized. Using the FD0002 sub-dataset, a health index (HI) was created, and models were trained. Once the models were trained, train and test HIs were estimated. The predicted test HI was matched with the predicted train HI based on a similarity-based approach, and then a RUL prediction was made. The results obtained were compared with the actual results to calculate the accuracy, and the algorithm that resulted in the maximum accuracy was identified. We selected six machine learning algorithms and also created an ensemble model by averaging the predictions of six machine learning algorithms for comparing prediction accuracy. The different algorithms were compared to obtain the prediction model with the closest prediction of remaining useful lifecycle in terms of the number of life cycles. This experiment showed us the effect of the similarity-based approach on the basic version of machine learning models for RUL prediction.

Jewelry of Eastern Lanna Identity: Strategies and Approaches for Contemporary Jewelry Design from Cultural Identity

Today’s jewelry designs look more contemporary, emphasizing self-expression by reflecting the perspectives and ideas of designers and artists in the context of society, culture, ethnicity, aesthetics, technology and ways of life through designs that are unique and in line with today’s lifestyles to create new artistic approaches. This research presents strategies and guidelines for designing contemporary jewelry from cultural capital by using the eastern Lanna area as a case study. The researchers conducted a unique analysis by studying the image and identity of the provinces in the eastern Lanna region, which led to the development of strategies and guidelines for jewelry design that reflect the eastern Lanna identity, as well as assessment of the perceptions of and satisfaction with jewelry prototypes designed by these strategies and such guidelines. The results showed that, in this research, the BLEND strategy was used in contemporary jewelry design, which was developed from the interpretation of the identity, image and characteristics of the provinces in the eastern Lanna group, into a design development in the form of a mixed design, or hybridization. These guidelines for creative design have generated design terms and conditions to present the value of work that expresses identity through four elements, namely 1) color, 2) materials, 3) patterns/shapes, and 4) story contents, which are synthesized through the perception of representative images to design and produce jewelry prototypes. The results of the evaluation of the jewelry prototypes as a whole revealed that the jewelry can express the eastern Lanna identity in an effective way, resulting in the creation of new knowledge in design, which is the development of concepts and processes to interpret new meanings in design in order to create value and worth as part of the utilization of cultural capital in the development of the country.

Implementation of cooling slots at the pressure side rims of squealer tips

The blade tip is a particularly critical component of the high pressure turbine due to the hot overtip leakage gas being responsible for efficiency losses and thermal degradation, often limiting engine life. Squealer tip designs reduce the over-tip leakage mass flow, increasing efficiency, but the thin pressure side rims can be vulnerable to damage because of their large surface area and the difficulties of shielding them from hot overtip leakage flow. This paper considers a new approach to cooling these pressure side rims, by employing an inclined slot inside a recessed step. Compared to conventional cooling strategies, in which coolant is provided by multiple cylindrical holes, the slot feature improves cooling effectiveness by more than 50% in key regions of the pressure side rim, whilst also allowing for a substantial reduction in coolant mass flow. The concept design is developed and explored using Computational Fluid Dynamics (CFD) calculations, and the performance is validated experimentally in a linear cascade with representative Mach and Reynolds numbers.

Efficacy of digital interventions for smoking prevention among children: a systematic review

Abstract Background Smoking remains a leading preventable cause of morbidity and mortality globally, with initiation often occurring in childhood. Early smoking onset is linked to increased difficulty in quitting and higher risk of long-term health complications. Traditional prevention strategies have not fully succeeded in curbing youth smoking rates, highlighting the need for innovative approaches. Digital interventions (DI), such as gamified education, social media campaigns, and virtual reality, offer a novel avenue for engagement and education. This systematic review aims to assess the efficacy of DI in preventing smoking, and improving knowledge and awareness about smoking damages, among children. This review is part of the PRIN project, whose goal is to evaluate the effectiveness of a DI aimed at school-aged children, intended to increase knowledge about the negative effects of smoking and prevent its use. Methods On the 18th of March 2024, PubMed, Scopus, and PsycINFO were surfed for trials and observational studies evaluating DI for smoking prevention among children aged 6-12 years. Study quality will be evaluated using the Cochrane Risk of Bias Tool and New Castle-Ottawa scale. The protocol has been registered in PROSPERO. Results From 3,081 initially identified articles, 328 papers were removed because duplicate. The screening process is ongoing. Conclusions DI are a promising tool for engaging young populations through platforms they are familiar with and receptive to. By leveraging the high penetration of digital technology in the daily lives of children, these interventions have the potential to deliver smoking prevention messages in a compelling and interactive manner. Understanding the effectiveness of DI in smoking prevention can significantly contribute to public health by providing viable alternatives to traditional methods and potentially reducing future smoking-related health burdens. Key messages • Evaluating digital strategies for smoking prevention among children could offer vital alternatives to traditional methods, potentially reducing long-term health risks. • Digital interventions (DI) offer promising new ways to engage young audiences on smoking prevention using familiar platforms, potentially reshaping public health approaches.

Data governance challenges on smart home involving multiple research sites

Abstract Background The development of Ambient Assisted Living (AAL) technology has great potential for ubiquitous health monitoring through collaboration between multiple research sites, but its use poses significant challenges to data governance. This study aims to investigate data governance challenges arising when smart home data flows across different research sites. Methods A four-analytic-dimension method was used to identify potential data-related issues that may occur when heterogeneous smart home data moves around multiple research sites. These dimensions include data domain, stakeholders, value, and governance goal. Results Data domain has difficulty in categorizing new data types generated by analytical models without a specified agreement, and determining the regulations for varying levels of anonymization and privacy protection is unclear in the AAL research field. Stakeholders in the AAL project may hold have different norms and practices for data use. Although some common values may be shared, such as improving the quality of homecare, conflicts may still arise and need to be regulated by data governance. Shifting AAL data between stakeholders may reduce its value, as different stakeholders may have varying interests. For instance, removing identifiable information from data to preserve privacy may reduce its value for researchers exploring individuals’ activity patterns. Governance goals are objectives for maintaining and facilitating data. While some governance goals can be widely acknowledged and shared, such as ensuring data security and privacy, conflicts may still exist over others, such as data access. Conclusions The big data generated by smart home technology highlights the need to develop proper data governance models to regulate data. This study’s implications include a better understanding of potential data-related challenges when data flows around multiple research sites, helping policymakers set up suitable data governance models. Key messages • AAL tech for health monitoring poses data governance challenges due to varying stakeholder norms and values. • Proper data governance models need to be developed for AAL data as it remains challenges in data domain, stakeholders, value, and governance goal.

Microalgae–Nanoparticle Systems as an Alternative for Biogas Upgrading: A Review

Anaerobic digestion is a well-established technology for the sustainable production of biogas. However, to be used as a substitute for natural gas or as vehicle fuel, it is necessary to remove carbon dioxide (CO2) and other contaminants from biogas that can compromise the useful life of combustion engines. Upgraded biogas is known as biomethane (&gt;95% methane content). This work reviews the different technologies used for upgrading biogas, emphasizing microalgae–nanoparticle systems, representing a more sustainable and environmentally friendly system. Parameters affecting these systems performance are discussed, and the trends and areas of opportunity for subsequent work are evaluated through a bibliometric analysis.

Optimalisasi Preventive Maintenance Ground Power Unit pada Perawatan Pesawat Udara di PT. IAA AMO Menggunakan Metode FMEA

High operational costs and downtime risks can affect industry efficiency making equipment maintenance optimization an urgent need. PT. IAA AMO, as a manufacturing industry in the field of aircraft maintenance, faces significant challenges with the low reliability of Ground Power Unit (GPU) engines which only reaches 86%. This has led to an increase in the company's operating costs. The purpose of this study is to optimize Preventive maintenance on the Ground Power Unit (GPU) in aircraft maintenance at PT. IAA AMO using the Failure Mode and Effect Analysis (FMEA) method. The results show that the MTTF of the GPU is 311 hours, while the MTBF is 373 hours. To prevent sudden breakdowns, preventive maintenance is recommended every 311 hours for non-repairable components and 373 hours for repairable components. This research offers a more effective maintenance strategy to improve GPU reliability and lower operational costs. This research results in more effective maintenance planning, which not only minimizes downtime and operational costs, but also improves the overall reliability of the GPU machine. With the implementation of FMEA methods and the right preventive maintenance strategy, companies can anticipate breakdowns early, extend engine life, and ensure smooth operations in support of aircraft maintenance.

PERENCANAAN PEMBELAJARAN PAI BERBASIS HIGHER ORDER THINKING SKILLS (HOTS) DI ERA SOCIETY 5.0: STRATEGI DAN IMPLEMENTASI

The Society 5.0 era, which is characterized by the integration of smart technology in everyday life, demands significant changes in educational practices, including Islamic Religious Education (PAI). To answer this challenge, PAI needs to integrate Higher Order Thinking Skills (HOTS) into its curriculum, with the aim of producing students who not only understand religious teachings but also have critical, creative and solution thinking skills. Strategies such as a contextual learning approach that links Islamic teachings with social issues and the use of digital technology can be used to strengthen the learning process.Research shows that implementing HOTS has a positive impact on students' critical thinking and problem solving abilities. However, challenges remain, including limited teacher knowledge about the HOTS method and inadequate technological facilities. Therefore, continuous teacher training and support from technological facilities are needed to ensure that technology-based learning can run effectively

DYNAMIC SIMULATION OF RUBBER PRODUCTION SYSTEMS USING SSM AND VENSIM APPROACHES

One of the contributors to the agricultural sector, particularly in the plantation sub-sector, is the rubber industry, which accounts for 38.54% of Indonesia's rubber exports. This opportunity arises from the fact that 85% of rubber producers are smallholder farmers, while the remaining share is owned by state and private enterprises. Makmurman is an individual rubber business owner based in South Sumatra Province, with a 4-hectare rubber plantation that directly sells raw rubber to collectors. The rapid advancement of technology in modern life has led to increased use of elastic materials, thereby driving higher demand for rubber, especially in the automotive industry. As a result, Makmurman has experienced a surge in demand for raw rubber from collectors. However, Makmurman has been unable to meet this demand, likely due to the many variables involved in the production process and the sale of raw rubber, which have created challenges. To address these issues, a root cause analysis is conducted to identify the appropriate solution using the soft system methodology approach. Additionally, data processing is carried out using Vensim software to model the rubber production system in a real-world scenario. The results include the development of causal loop diagrams and stock flow diagrams. The expected outcome is a dynamic system simulation with various scenarios, ultimately identifying the best scenario that ensures the highest availability of rubber for Makmurman to meet the demands of the rubber collectors.

THE TRAINING OF TEMPERATURE MONITORING SYSTEM WITH LM35 SENSOR BASED ON RESBEERY PI

Abstract. This community service activity aims to train the community on developing and implementing a temperature monitoring system using the LM35 sensor integrated with Raspberry Pi. This training was carried out to improve people's understanding and skills, especially in utilizing microcontroller-based technology and IoT (Internet of Things) in daily life, especially in the field of room temperature or environmental monitoring. This activity involves targets, for example, teachers, students, and technicians, at SMA AL-IRSYAD TEGAL, with training methods that include basic theories about temperature sensors, introduction to Raspberry Pi, and hands-on practice in assembling and programming temperature monitoring systems. The results of this training showed that participants could understand the basic concepts of temperature monitoring systems and could apply the knowledge gained in making simple devices that can measure and display temperature in real time. The activity evaluation showed that most of the participants felt helped by this training and showed high interest in further developing the system that had been studied. In the future, it is hoped that similar activities can continue to be carried out to empower the community to utilize technology for daily needs. Keywords: Community service, temperature monitoring system, LM35, Raspberry Pi, technology training.

An aero-engine remaining useful life prediction model based on clustering analysis and the improved GRU-TCN

Abstract Accurately predicting the remaining useful life (RUL) of engines is paramount for implementing effective preventive maintenance strategies, preventing injuries and fatalities caused by equipment failures, and significantly reducing routine repair and replacement costs. However, existing deep learning models often ignore the variable operating conditions in real engineering applications and do not sufficiently consider the interaction between time series and degradation laws, which directly leads to the inability to effectively extract to degradation feature extraction. To address this problem, this study developed a novel combined network model named CA-DRGRU-TTCN, aimed at accurately predicting the RUL of engines. Firstly, a Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is used to identify multiple operating conditions, and incorporate the recognition results into the model as additional new features. The first degradation time point is determined by JS divergence. Secondly, the deep connectivity of the residual Gated Recurrent Unit (GRU) module is designed to extract deeper degradation features, and an improved TMSE loss function based on the first degradation time point is applied to Temporal Convolutional Networks (TCN) to better capture the dependency between the time series and the real degradation degree of the engine. Finally, experiment results on the C-MAPSS dataset show that the proposed method achieves better performance compared to existing state-of-the-art methods.&amp;#xD;

Scientific interest in rehabilitation: a bibliometric analysis

Purpose: It is aimed to conduct bibliometric analysis to explore scientific interest in rehabilitation. The date of bibliometric analysis was 17.01.2023, and a total of 410.000 documents from all times to this date were analyzed. Materials and Methods: The data for this study was obtained from Scopus, a multidisciplinary database, for the period of sixty-two years (1960-2022) using the keyword ‘rehabilitation’. Our bibliometric analysis includes articles, authors, subject area, document types, countries, languages, affiliations, publication years, citations, and number of citations. Since Scopus allows the download of 2000 data at a time, citation reports after 2021 were examined. Results: 109,138 of 410.000 articles were in all open Access and 342.918 were in English. When we look at the distribution of the number of articles by year, there were 10,095 articles in 2023, 27,615 articles in 2022, 25,594 articles in 2021, and 22,718 articles in 2020. Documents types were; article (72.5%), conference paper (9.9%), review (9.8%), book chapter (2.3%), and editorial (1.7%). Documents according to subject areas were as follows; Medicine (N=282.301), Health Professions (N=66,434), Engineering (N=53,704), Neuroscience (N=26,016), Computer Science (N=25,326), Social Sciences (N=23,080), Psychology (N=21,384), Nursing (N=19.481). A total of 199 cited documents have been reached. Sixty-two in 2023; 132 in 2022; 5 in 2021. The h index was 4. Conclusion: We see that 'Rehabilitation' is increasingly becoming an area of interest for many different disciplines, as developing technology and quality of life in the field of health are at the forefront of treatment approaches.