User Comfort Research Articles

Heat load forecasting model considering two dimensional changes of time series

The regulation strategy of a district heating system is adjusted based on accurate heat load prediction, which not only effectively reduces energy consumption but also improves system efficiency and user comfort. In order to improve the accuracy of heat load forecasting, a heat load forecasting model considering the two-dimensional change of time series is introduced in this paper. Firstly, the original heat load data is denoised by SVMD decomposition, and several stationary and regular modal components are obtained. Then, three strategies were used to enhance the BWO algorithm, and the IBWO-TimesNet prediction model was established to extract the hidden information of time series data from a two-dimensional perspective. Finally, the prediction performance of the model is evaluated in detail through case analysis. The results show that MAE, RMSE and R2 of SVMD-IBWO-TimesNet model are 0.647, 1.190 and 99.1%, respectively. Compared with other mainstream prediction models, this model has higher prediction accuracy. In addition, even if the training samples are reduced, the SVMD-IBWO-TimesNet model can still effectively predict the heat load and has strong generalization ability. Therefore, the performance of the model is verified, which provides a reference for the accurate control of heat load. Practical application Heat load forecasting is a vital task particularly in relation to its impact on the management of building energy efficiency. The contribution of this paper is to provide a heat load forecasting model based on advanced algorithms and data analysis. This insight derived from advanced modelling will assist professionals in the pursuit of more accurate prediction of the heat needs of buildings, thereby optimizing the design and operation of heating systems. The practical application of this technology could save energy costs, reduce carbon emissions, and improve the comfort and sustainability of buildings.

An evaluation of a bespoke modified UCBL foot orthosis on subjects with flat foot using kinetic measurements and user comfort scores: A randomized controlled trial

AimThe purpose of this study was to assess and evaluate the effect of a bespoke Modified UCBL Foot Orthosis (MUFO) using both kinetic parameters (Centre of Pressure (CoP) and the Ground Reaction Force (GRF) pattern) and comfort scores in subjects diagnosed with flat foot. MethodThis study included thirty-four young adults with symptomatic flatfeet. Two Kistler force plates (100 Hz) were used to record the CoP sway and GRF pattern during four conditions; 1) an MUFO and standard-fit shoe; 2) the University of California-Berkley Lab (UCBL) insole and standard-fit shoe; 3) barefoot and 4) standard-fit shoe only. The magnitude of subject comfort with UCBL and MUFO also was measured by a 10 cm Visual Analogue Scale (VAS) during walking. ResultsThe MUFO decreased mean lateral displacement in the initial phase and midstance of gait compared to barefoot walking. During the propulsion phase use of the new MUFO produced more lateral excursion with a mean difference of 3 mm) P < 0.001(compared to barefoot walking and standard shoe wear. No significant difference in comfort rate was found between the MUFO and UCBL (P = 0.165). ConclusionThe MUFO produced effective pronation control and decreased the CoP displacement in all of stance phase.

Materials, Structure, and Interface of Stretchable Interconnects for Wearable Bioelectronics.

Since wearable technologies for telemedicine have emerged to tackle global health concerns, the demand for well-attested wearable healthcare devices with high user comfort also arises. Skin-wearables for health monitoring require mechanical flexibility and stretchability for not only high compatibility with the skin's dynamic nature but also a robust collection of fine health signals from within. Stretchable electrical interconnects, which determine the device's overall integrity, are one of the fundamental units being understated in wearable bioelectronics. In this review, a broad class of materials and engineering methodologies recently researched and developed are presented, and their respective attributes, limitations, and opportunities in designing stretchable interconnects for wearable bioelectronics are offered. Specifically, the electrical and mechanical characteristics of various materials (metals, polymers, carbons, and their composites) are highlighted, along with their compatibility with diverse geometric configurations. Detailed insights into fabrication techniques that are compatible with soft substrates are also provided. Importantly, successful examples of establishing reliable interfacial connections between soft and rigid elements using novel interconnects are reviewed. Lastly, some perspectives and prospects of remaining research challenges and potential pathways for practical utilization of interconnects in wearables are laid out.

Partisi Ruang Berdasarkan Kebutuhan Pengguna Dengan Konsep Industrial

Along with the development of the era, human desires for housing are increasingly diverse, where houses are not only for carrying out daily activities and carrying on life, but also become a means of inspiration and indicate social levels in the community. The design object to be appointed is the residence of Mr. Antok Suharno which is located in the village of Mulyorejo, Mojosongo District, Boyolali Regency. The residence previously did not have a concept, the Industrial concept became the design theme plan to be implemented. The design objective is to create privacy for the living room and dining room that meets user comfort in accordance with the comfort theory by presenting a partition, functioning as a separator as well as maintaining privacy and presenting decorative value between the living room and dining room. The data collection method is by surveying, measuring and documenting the location of Mr. Antok Suharno's residence, collecting user data for each room and interviewing Mr. Antok Suharno as the owner of the house. Partitions designed to apply materials in accordance with the Industrial concept, namely with black hollow iron material, multiplex and vinyl finishing with wood motifs. The results of the partition design have a length of 180cm, a width of 30cm and a height of 200cm.

Urgency of District Head’s Policy in the Implementation of the Use of Trotoar and Edge of the “Jalan Bj Habibie” In Bone Bolango District of Gorontalo

This article analyzes the right policies to avoid the occurrence of criminalization, traffic congestion, environmental cleanliness that is not maintained and irresponsible behaviour along the sidewalks and curbs of Prof. B.J Habibie, Bone Bolango district. The policy of the regional head in making the function of the roadside and sidewalk useful for the community is a necessity or a necessity to protect the public from the disturbance of security, comfort, and order. No matter how good the existence of roads and sidewalks without being supported by government policies in their utilization, it will not guarantee the comfort of the user community, because, without a policy that guarantees safety and comfort for users and the community, the facilities built will bring disaster to the community and facility users. Keywords: policy, district head, public facility, road facility, Bone Bolango

Fabric and Fiber-Integrated, Washable Hydrogel Electrodes for Clinically Accurate Sleep Monitoring in-Home

Longitudinal tracking of sleep metrics is important for detecting and managing various diseases, spanning cardiorespiratory disorders to dementia. However, at present, sleep monitoring primarily occurs in specialized medical facilities that are not conducive to longterm studies. In-home solutions either compromise user comfort or signal accuracy in tracking sleep variables and have not yet provided reliable longitudinal data. We believe that human-centered design of multimodal, low-form-factor, comfortable sensing systems is needed for this increasingly-important area of preventative health monitoring. Our lab developed a suite of fabric-based and/or garment-integrated sensors and sensing modalities that accurately and reliably extract important sleep metrics, such as posture, cardiorespiratory signals, eye movement and brain activity, over the course of an eight-hour sleep session. Our garment-integrated sensing arrays do not require a medical professional for on-body positioning, maintain their function independent of sizing and fit on individual users, and can be laundered or cleaned with antibacterial wipes without compromising its varied sensing elements. Here, we describe one of these two key sensors, a fabric or fiber-based electrochemical hydrogel electrode that enables wearable biopotential monitoring, including electrocardiography (ECG), eletrooculography (EOG) and electroencephalography (EEG), from which the aforementioned sleep metrics can be recorded and quantified with clinical precision and accuracy. The hydrogel is fabricated as a coating on either commodity fabrics or threads using a low-temperature reactive deposition process, termed photoinitiated chemical vapor deposition (piCVD), during which hydrogel monomers react with a photoinitator in the vapor phase to create a polymeric hydrogel coating directly on the surface of fabrics or threads that have been temporarily surface modified with a skin-safe electrolyte gel. The resulting composite hydrogel coating isolated from this operation is ionically conductive, can be reversibly swelled in water and dried without losing ionic conductivity, and transduces the ionic signals (fluxes) experienced by the body into an electrical signal that can be captured by any commercial ECG, EOG or EEG monitoring instrument. An array of these fabric or thread-based hydrogel electrodes can be integrated into readily-available garments using simple cut-sew techniques and these garments can then be worn throughout the night to effect continuous ECG, EOG and EEG monitoring at home. Design elements of a custom-made circuit board that allows simultaneous capture of these signals will be described. Results from an ongoing user study of >50 adults will be presented to validate the clinical precision and accuracy of these garment sensor for sleep quality monitoring.

Analysis of Traffic Impact Due to Construction of Village Government Offices on MT Haryono Road Samarinda City, Indonesia

Development of the Village Government Office Area located on MT. Haryono Street Samarinda City based on Minister of Transportation Regulation no. 17 of 2021 is included in the Low Andalalin category, where the development activities do not have a significant impact on traffic on roads and intersections. The results of the analysis by modeling the increase in traffic growth each year also did not cause a significant decrease in the performance and level of service of a road section or intersection. However, to create sustainable and well-implemented development, efforts are made to maximize the level of safety and comfort for road users around the activity area using vehicle circulation, pedestrian facilities, signs or markings, and traffic engineering management. as well as other safety and comfort supporting facilities. Considering that Andalalin is a requirement that is integrated with the Amdal study in arranging a Building Construction Permit (IMB), the initiator must take care of the traffic impact analysis recommendations, which of course apart from maintaining human and environmental safety is also an administrative requirement that must be fulfilled.

BIM-Based Strategies for the Revitalization and Automated Management of Buildings: A Case Study

This study explores the transformative potential of integrating Building Information Modeling (BIM) and Generative Design methodologies in heritage conservation and building management. By utilizing BIM, detailed architectural, structural, and MEP models were created, facilitating precise design and effective stakeholder collaboration. Generative Design enabled the exploration of multiple design solutions, optimizing spatial layouts and structural integrity. The project also integrated automated management systems and IoT sensors to enhance real-time monitoring, energy efficiency, and user comfort through the development of a digital twin. Despite encountering challenges such as technical complexities and budget constraints, the project successfully preserved the cinema’s historical essence while incorporating modern functionalities. The findings highlight the contributions of BIM and Generative Design to the AEC industry, emphasizing their role in improving design accuracy, operational efficiency, and sustainability. This research provides valuable insights for future projects in heritage conservation, offering a blueprint for balancing historical preservation with contemporary needs. The revitalization of the “Ex Cinema Santa Barbara” in Paternò exemplifies these advancements, demonstrating how these technologies can restore and modernize culturally significant historical buildings effectively.

Day-ahead optimal scheduling considering thermal and electrical energy management in smart homes with photovoltaic–thermal systems

The environmental impact on the energy sector has become a significant concern, necessitating the implementation of Home Energy Management Systems (HEMS) to enhance the energy efficiency of buildings, reduce costs and greenhouse gas emissions, and ensure user comfort. This paper presents a novel approach to provide optimal day-ahead energy management plans in smart homes with Photovoltaic/Thermal (PVT) systems, aiming to achieve a balance between energy cost and user comfort. This multi-objective problem employs the Non-dominated Sorting Genetic Algorithm III as the optimization algorithm and the Nonlinear Auto-regressive with External Input to forecast the day-ahead meteorological variables, which serve as inputs to predict the PVT electrical and heat production in the thermal resistance model. The HEMS benefits from the time-of-use tariff due to the flexibility provided by the energy storage from a battery bank and a boiler. Furthermore, it performs a load scheduling for 10 controllable loads based on three feature parameters to characterize occupant behavior. A study case analysis revealed a cost reduction of approximately 66% in the solution close to the knee of the Pareto curve (S3 solution). The environmental impact on the energy sector has become a The PVT heat production was sufficient to meet the thermal demand of the showers. The proposed hybrid battery management model effectively eliminated the export of electricity to the grid, reducing consumption during peak periods and the maximum peak demand.

Classification of Temperature and Humidity in Green Open Spaces by Implementing Internet of Things (IoT) using Mamdani Fuzzy Logic

The condition of green open spaces plays a pivotal role in influencing the comfort and well-being of users engaged in various activities within these environments. Hydrological and microclimate factors, particularly temperature and humidity, hold significant sway over the ecological balance in these areas. This study addresses the need for a tool to assess air temperature and humidity, facilitating public access to critical environmental data that impacts the psychological well-being of living organisms. In pursuit of this objective, a comprehensive monitoring system harnessing the power of the IoT was developed. This system integrates DHT22 and MQ-9 sensors to monitor temperature, humidity, and CO2 gas levels within multiple green open spaces. Data from these sensors is transmitted to a central database with minimal time delays: 2 seconds from the sensors to the server, 1 second from the server to the application, and 3 seconds from the hardware to the application. Impressively, this data transmission achieved a 100% success rate. To assess the comfort levels of these green open spaces, the system employs fuzzy Mamdani logic. It processes data obtained from the DHT22 sensor, using predefined temperature and humidity value thresholds. This innovative monitoring system provides valuable insights into the environmental conditions of green open spaces, contributing to the enhancement of the overall quality and suitability of these areas for various activities.

A Compact Wearable Textile Antenna for NB-IoT and ISM Band Patient Tracking Applications.

This paper proposes a novel multi-band textile monopole antenna for patient tracking applications. The designed antenna has compact footprints (0.13λ02) and works in the narrow band-internet of things (NB-IoT) 1.8 GHz, radio frequency identification (RFID), and industrial, scientific, and medical (ISM) 2.45 GHz and 5.8 GHz bands. The impedance bandwidths and gain of the antenna at 1.8 GHz, 2.45 GHz, and 5.8 GHz are 310 MHz, 960 MHz, and 1140 MHz; 3.7 dBi, 5.3 dBi, and 9.6 dBi, respectively. Also, the antenna's behavior is checked on different body parts of the human body in various bending scenarios. As per the evaluated link budget, the designed antenna can easily communicate up to 100 m of distance. The specific absorption rate values of the designed antenna are also within acceptable limits as per the (FCC/ICNIRP) standards at the reported frequency bands. Unlike traditional rigid antennas, the proposed textile antenna is non-intrusive, enhancing user safety and comfort. The denim material makes it comfortable for extended wear, reducing the risk of skin irritation. It can also withstand regular wear and tear, including stretching and bending. The presented denim-based antenna can be seamlessly integrated into clothing and accessories, making it less obtrusive and more aesthetically pleasing.

Analisis Kerusakan Jalan dengan Metode PCI Untuk Jalan Jati Kota Palangka Raya

A fully functional road facilitates the movement of people from one place to another, yet road damage can pose threats to the safety and comfort of users. Jati Road serves as a secondary collector road connecting residential centers. The density of traffic on this route is high due to the presence of residential areas and schools nearby. Damage to Jati Road can have a negative impact on the road users' experience. This research aims to determine the types and levels of damage using the PCI method. The study was conducted directly on Jati Road by dividing it into several sections, each spanning 100 meters. Each segment was then visually inspected and measured to identify any damage. The research findings indicate that the PCI of Jati Road in Palangka Raya City reached 73.19%, which is considered very good.

The technological assessment of green buildings using artificial neural networks

This study aims to construct a comprehensive evaluation model for efficiently assessing appropriate technologies within green buildings. Initially, an Internet of Things (IoT)-based environmental monitoring system is devised and implemented to collect real-time environmental parameters both inside and outside the building. To evaluate the technical suitability of green buildings, this study employs a multifaceted approach encompassing various criteria, including energy efficiency, environmental impact, economic benefits, user comfort, and sustainability. Specifically, it involves real-time monitoring of environmental parameters, analysis of energy consumption data, and indoor environmental quality indicators derived from user satisfaction surveys. Subsequently, a Multi-Layer Perceptron (MLP) is selected as a conventional artificial neural network (ANN) model, while a Long Short-Term Memory (LSTM) model is chosen as an advanced recurrent neural network model in the realm of deep learning. These models are utilized to process and explore the collected data and assess the technical suitability of green buildings. The dataset comprises physical quantities such as temperature, humidity, and light intensity, as well as economic indicators including energy efficiency and building operating costs. Furthermore, the assessment process considers the building's life cycle assessment and indoor environmental quality factors such as health, comfort, and safety. By incorporating these comprehensive criteria, a holistic evaluation of green building technologies is achieved, ensuring the selected technologies' suitability and effectiveness. The model prediction results demonstrate that the proposed hybrid evaluation model exhibits high accuracy and robust stability in predicting building environmental parameters. For instance, the Root Mean Square Error (RMSE) for temperature prediction is 1.2 °C, the Mean Absolute Error (MAE) is 0.9 °C, and the determination coefficient (R2) reaches 0.95. Similarly, for humidity prediction, the RMSE, MAE, and R2 are 3.5 %, 2.8 %, and 0.88. Compared to the traditional MLP and LSTM models alone, the proposed hybrid model shows significant improvements in predicting building energy consumption, with approximately 15 % and 12 % reductions in RMSE and MAE, respectively, and an increase in R2 values of approximately 7 percentage points. These findings indicate that by amalgamation of the IoT and ANNs, this study successfully establishes a comprehensive model for accurately assessing technologies suitable for green buildings. This approach offers a novel perspective and methodology for the design and evaluation of green buildings.

CNN-LSTM for MFCC-based Speech Recognition on Smart Mirrors for Edge Computing Command

Smart mirrors are conventional mirrors that are augmented with embedded system capabilities to provide comfort and sophistication for users, including introducing the speech command function. However, existing research still applies the Google Speech API, which utilizes the cloud and provides sub-optimal processing time. Our research aim is to design speech recognition using Mel-frequency cepstral coefficients (MFCC) and convolutional neural network–long short-term memory (CNN-LSTM) to be applied to smart mirror edge devices for optimum processing time. Our first step was to download a synthetic speech recognition dataset consisting of waveform audio files (WAVs) from Kaggle, which included the utterances “left,” “right,” “yes,” “no,” “on,” and “off. ” We then designed speech recognition by involving Fourier transformation and low-pass filtering. We benchmark MFCC with linear predictive coding (LPC) because both are feature extraction methods on speech datasets. Then, we benchmarked CNN-LSTM with LSTM, simple recurrent neural network (RNN), and gated recurrent unit (GRU). Finally, we designed a smart mirror system complete with GUI and functions. The test results show that CNN-LSTM performs better than the three other methods with accuracy, precision, recall, and an f1-score of 0.92. The speech command with the best precision is "no," with a value of 0.940. Meanwhile, the command with the best recall is "off," with a value of 0.963. On the other hand, the speech command with the worst precision and recall is "other," with a value of 0.839. The contribution of this research is a smart mirror whose speech commands are carried out on the edge device with CNN-LSTM.

Exploring the effects of landscape interventions on outdoor thermal comfort using digital simulation

Abstract The assessment of outdoor thermal comfort plays an important role in design decisions and encourages better planning and development of outdoor environments. This study explores the potential effects of landscape interventions on outdoor thermal comfort, testing two thermal comfort indicators on a selected hospitality development. Results are crucial factors to consider as the success of hospitality developments and its outdoor spaces are dependent on how visitors perceive and interact with them. Digital simulations were conducted using Rhinoceros software and the Grasshopper tool to produce heat maps. For the purpose of the study, two sets of simulations were developed to examine changes in the Universal Thermal Climate Index (UTCI) and Incident Radiation of the site – a) buildings alone and b) with landscape elements. As a result, UTCI with landscape intervention decreased by 2°C while Incident Radiation is significantly lower throughout spaces provided with shading elements. Results of UTCI simulations still deliver strong heat stress to occupants, while Incident Radiation has considerably improved with landscape interventions. The provision of shading elements helped lessen solar radiation penetrating the site, thus improving the thermal comfort of users. Wind velocity showed minimal effects on perceived heat based on the UTCI assessment scale. Nonetheless, improvement in the planning and orientation of buildings and strategic provision of demountable sun shading elements in future developments are recommended to allow better air circulation.

Comfort evaluation and physiological effects/autonomic nervous system response of inflatable deep pressure vest in reducing anxiety

BackgroundDeep pressure therapy treats anxiety by triggering physiological responses and promoting calmness. Moreover, measuring user comfort can improve product quality. ObjectiveTo investigate the physiological effects and subjective comfort level of inflatable deep pressure vests to enhance their calming effect. MethodsExperimental research was conducted with a one-group pretest-posttest design for physiological effects using pulse oximetry for peripheral pulse rate and a one-shot case study for three subscale parameters that help evaluate comfort (pressure, touch, and mobility) using the Numerical Rating Scale (NRS). Deep pressure intervention using the Inflatable Vest was performed for three sessions, each lasting 5 min. ResultsThis study was conducted with 46 participants (24 males, 22 females) aged 17–20 (19.52 ± 0.78). Although pulse rate consistently decreased in all sessions, session 1 showed a significant decrease (p = 0.014*, d = 0.379), whereas sessions 2 (p = 0.274, d = 0.163) and 3 (p = 0.597, d = 0.078) demonstrated non-significant decreases with small effect sizes. The pressure comfort subscale showed that 87.0 %, 4.3 %, and 8.7 % of the participants, and the touch comfort subscale test revealed that 82.6 %, 8.7 %, and 73.9 % of the participants rated it as comfortable, very comfortable, and less comfortable, respectively. The mobility subscale test showed that 73.9 % of the participants rated no limitation, 17.4 % rated somewhat limited, and only 8.7 % rated limitation. Decreased pulse rate and pressure comfort were significantly positively correlated (r = 0.282**, p < 0.01), whereas touch pressure and mobility were not (r = 0.160, p > 0.05; and r = 0.121, p > 0.05, respectively). Decreased pulse rate was also positively correlated with the overall score for the three aspects (r = 0.201*, p < 0.05) ConclusionsA comfortable inflatable deep pressure vest provides a physiologically calming effect for therapeutic modalities.

Research progress in home energy management systems consideration of comfort

According to statistics, the carbon dioxide emissions from Chinas power industry account for about 40% of the total energy consumption and carbon dioxide emissions, while residential electricity consumption accounts for 36.6% of the total social electricity consumption. However, ordinary households have low electricity efficiency and serious waste. In the context of the national strategy of carbon peak and carbon neutrality, the Home Energy Management System (HEMS) has been introduced to improve household electricity efficiency, reduce electricity consumption, and achieve energy conservation and emission reduction while ensuring the comfort of residents. This article introduces the current research status of home energy management systems that take into account user comfort, and shows some optimization models for home energy management systems that take into account user comfort. It specifically elaborates on the optimization models for household appliances and comfort, briefly outlines the relatively trendy load prediction and scheduling optimization models, and proposes some suggestions and prospects for popularizing knowledge related to home energy management systems for family members using smart homes and temperature comfort modeling based on the current development status.

Reinforcement learning layout‐based optimal energy management in smart home: AI‐based approach

AbstractThis research addresses the pressing need for enhanced energy management in smart homes, motivated by the inefficiencies of current methods in balancing power usage optimization with user comfort. By integrating reinforcement learning and a unique column‐and‐constraint generation strategy, the study aims to fill this gap and offer a comprehensive solution. Furthermore, the increasing adoption of renewable energy sources like solar panels underscores the importance of developing advanced energy management techniques, driving the exploration of innovative approaches such as the one proposed herein. The constraint coordination game (CCG) method is designed to efficiently manage the power usage of each appliance, including the charging and discharging of the energy storage system. Additionally, a deep learning model, specifically a deep neural network, is employed to forecast indoor temperatures, which significantly influence the energy demands of the air conditioning system. The synergistic combination of the CCG method with deep learning‐based indoor temperature forecasting promises significant reductions in homeowner energy expenses while maintaining optimal appliance performance and user satisfaction. Testing conducted in simulated environments demonstrates promising results, showcasing a 12% reduction in energy costs compared to conventional energy management strategies.

Visual Communication Design of Mobile App Interface Based on Digital

With the obvious trend of population aging, the demand of digital products for the elderly is increasing, and the visual design of APP interface is very important for the user experience of the elderly. This study will focus on how to design and optimize the interface through visual communication to enhance the application experience of elderly users. Through a comprehensive analysis of the design principles, user characteristics and use requirements of the aging reading APP, this paper discusses how to design skillfully in the aspects of color application, picture selection, typesetting layout and interactive operation, so as to create an interface that conforms to the reading habits of elderly users. Through the discussion of this study, the purpose is to provide designers and related practitioners with practical guidance and inspiration for the design of aging APP interface for elderly users. The primary aim is to advance digital product design towards a more human-centered and universally accessible direction, enhancing convenience and comfort for elderly users.

Open-source design of low-cost sensorised elastic actuators for collaborative prosthetics and orthotics

Collaborative robots, or cobots, have become popular due to their ability to safely operate alongside humans in shared environments. These robots use compliant actuators as a key design element to prevent damage during unintended collisions. In prosthetic and orthotic applications, compliant actuators are crucial for ensuring user safety and comfort. However, most compliant cobots for these applications are excessively expensive and complex to construct. Our study introduces an innovative, cost-effective, and sensorised elastic actuator design tailored for prosthetics and orthotics. The design uses a modular approach and leverages 3D printing technology for rapid customisation, enabling efficient and affordable fabrication. Both hardware and software components are open-source, facilitating unrestricted access for students, researchers, and practitioners. Our design supports impedance and admittance control techniques, enhancing the system’s capabilities. Validation results show a standard deviation of 9.67 Nm between calculated and measured torque in impedance control and 0.2563 radians between calculated and measured angles in admittance control. This allows for improved adaptability to varying operational requirements in prosthetics and orthotics. By introducing this educational framework encompassing a low-cost, sensorised elastic actuator design, we aim to address the need for accessible solutions in the field of collaborative robotics for prosthetics and orthotics.