System Performance Assessment Research Articles

Enhanced operation of PVWPS based on advanced soft computing optimization techniques

This study introduces three soft computing (SC) optimization algorithms aimed at enhancing the efficiency of photovoltaic water pumping systems (PVWPS). These algorithms include the Gorilla Troop Algorithm (GTO), Honey Badger Algorithm (HBA), and Snake Algorithm (SAO). The goal of the SC optimizers is to maximize the output power of the PV array (PPV) and enhance the efficiency of the DC motor (η), thereby optimizing the water flow rate (Q) of the pumping system. The analytical modeling approach proposed in this study involves forecasting the optimal duty cycle (Dop) for a buck-boost converter, taking into account variables such as solar radiation (G) and ambient temperature (T). A comparative analysis is conducted between the suggested SC optimizers and analytical modeling. MATLAB simulation is employed to explore an adaptive neuro-fuzzy inference system (ANFIS) trained for the proposed system. The objective is to assess system performance and accuracy. Findings indicate a strong convergence between the analytical model and the simulation model utilizing SC optimizers. Moreover, the neuro-fuzzy system trained offline, coupled with the proposed SC optimizers, demonstrates superior performance compared to traditional control methods like perturb and observe (P&O) and incremental conductance (IC). This superiority is evident across various metrics including motor efficiency (η), photovoltaic (PV) output power (PPV), water flow rate (Q), and time response.

Real-time safety and worker self-assessment: Sensor-based mobile system for critical unsafe behaviors

Human error significantly contributes to construction accidents, exacerbated by the lack of a digital tool for assessing and improving workers' safety performance. This paper addresses this gap by developing: 1) a Real-Time Safety Performance Assessment and Report System; 2) a Safety Behavior Self-Assessment and Improvement System; and 3) a Sensor-Based Safety Performance Analytic Mobile System (SBSPAMS) to detect, assess, and modify workers' unsafe behaviors. Through a comprehensive literature review, this paper developed a real-time safety performance assessment method, a safety behavior self-assessment questionnaire, and tailored recommendations for workers' safety performance improvement. The SBSPAMS was developed by integrating the safety performance assessment and safety behavior self-assessment functions into a Sensor-Based Safety Monitoring Mobile System (SBSMMS), along with a framework for the practical implementation of the SBSPAMS. This paper enriches construction safety knowledge by providing a performance assessment and improvement approach and contributes to the construction industry by developing a tool for worker-oriented safety management.

Mapping of Health System Performance Indicators to the WHO HSPA Framework.

Healthcare systems worldwide face escalating costs and demographic changes, necessitating effective evaluation tools to understand their underlying challenges. Switzerland's high-quality yet costly healthcare system underscores the need for robust assessment methods. Existing international rankings often lack transparency and comparability, highlighting the value of structured frameworks like the Health System Performance Assessment (HSPA) by the World Health Organization (WHO). This framework evaluates healthcare systems across multiple dimensions including governance, resource generation, financing, and service delivery. This paper aims to integrate Swiss healthcare indicators from the Swiss Health Observatory (Obsan) into the HSPA framework, addressing the central research question: How can these indicators be mapped to the HSPA framework, and what insights does this integration provide? Our methodology includes selecting and categorizing Obsan indicators, manually mapping them to HSPA sub-functions, and validating these mappings using word embeddings and cosine similarity. An R Shiny application was developed for interactive visualization. Results demonstrate accurate indicator assignment, enabling intuitive visualization and enhancing data structuring.

Over-the-air testing of LTE-A PHY layer in reverberation chamber

Reliable, repeatable, and flexible testing is crucial for assessing system performance and ensuring the quality of communication. In reverberation chambers (RC), real-life propagation environments can be emulated by loading absorbers, facilitating controlled testing of the system. This work presents over-the-air (OTA) testing of the LTE-A PHY layer in the RC. We assessed the performance of the LTE-A link using key performance indicators (KPIs) such as error vector magnitude (EVM), bit error rate (BER), and signal-to-noise ratio (SNR) for varying transmitter (Tx) and receiver (Rx) gains. Additionally, we have compared the results both in an empty RC and when the RC was loaded with RF absorbers. We used software-defined radio (SDR) for OTA transmission of LTE-A frames. The measurement results indicate that loading the RC with RF absorbers improves EVM, BER, and SNR. We also quantified the performance of the LTE-A link by changing the position of RF absorbers. Results showed that loading absorbers yielded up to 72.8% improvement in EVM, and placing absorbers closer to Rx helped reduce the amount of multipath, resulting in better transmission performance.

Towards a System Dynamics Framework for Human–Machine Learning Decisions: A Case Study of New York Citi Bike

The growing number of algorithmic decision-making environments, which blend machine and bounded human rationality, strengthen the need for a holistic performance assessment of such systems. Indeed, this combination amplifies the risk of local rationality, necessitating a robust evaluation framework. We propose a novel simulation-based model to quantify algorithmic interventions within organisational contexts, combining causal modelling and data science algorithms. To test our framework’s viability, we present a case study based on a bike-share system focusing on inventory balancing through crowdsourced user actions. Utilising New York’s Citi Bike service data, we highlight the frequent misalignment between incentives and their necessity. Our model examines the interaction dynamics between user and service provider rule-driven responses and algorithms predicting flow rates. This examination demonstrates why understanding these dynamics is essential for devising effective incentive policies. The study showcases how sophisticated machine learning models, with the ability to forecast underlying market demands unconstrained by historical supply issues, can cause imbalances that induce user behaviour, potentially spoiling plans without timely interventions. Our approach allows problems to surface during the design phase, potentially avoiding costly deployment errors in the joint performance of human and AI decision-makers.

An efficient uncertainty analysis of performance of hydrogen storage systems

The metal hydride hydrogen storage systems are gaining popularity due to their high volumetric capacity, safety and stability. The designing of these systems is complex due to many reasons, including input uncertainties. The performances of these systems are often evaluated in deterministic framework, ignoring uncertainties. This includes over-conservative safety factors in the design process increasing time and costs involved in designs. The uncertainty analysis could be a better alternative to assess system performance under such scenarios. This study investigates– i) the effect of input uncertainties on uncertainties of multiple and implicit system outputs, i.e., reaction fraction and bed temperature, ii) application of response surface and Borgonovo’s global sensitivity analysis for efficient analysis, and iii) a comparative assessment between different uncertainty methods. The methodology is demonstrated for a space heating system. Initially, a surrogate relationship is constructed between inputs-outputs using moving least square response surface, based on known input-output data estimated using COMSOL for random input realizations. Next, the sensitive inputs were identified using Monte-Carlo simulations based Borgonovo’s analysis. Finally, the effect of uncertainties of sensitive inputs on outputs were estimated using different uncertainty methods. Harr’s and Hong’s (2n) point estimate methods were observed to be highly accurate, mathematically simpler and efficient, as compared to other methods. The uncertainties of outputs were directly dependent on uncertainties of sensitive inputs. The probabilistic safety measure, reliability index, estimated using output statistics was of significant practical utility for industries to avoid deterministic safety factors based over-conservative and costly designs of storage systems.

Seismic performance assessment of structural systems in the aftermath of the 2023 Kahramanmaraş earthquakes: Observations and fragility analyses

This article evaluates how different reinforced concrete (RC) building systems in Türkiye behaved during the extreme 2023 Kahramanmaraş earthquakes. The analysis relies on a comprehensive field survey covering 242 RC buildings across various heavily affected locations. Most surveyed buildings were low- and mid-rise RC moment frames and frame-wall (hybrid) systems, with RC wall construction being less commonly observed. Both RC frame and hybrid buildings exhibited several common deficiencies, resulting in significant structural and non-structural damage due to high drift demands. The performance of RC wall construction varied, with some buildings sustaining severe damage while others remained largely unaffected. An analysis of structural plans revealed that RC wall buildings with adequate wall amounts demonstrated exceptional performance, while those with inadequate amounts of walls experienced severe damage. In addition, fragility analyses using simplified models based on surveyed buildings reinforced these findings. The analyses suggested that RC frame and hybrid systems were insufficient in ensuring life safety during the earthquakes. Conversely, properly designed RC wall buildings are expected to perform well. This alignment between field observations and fragility analyses underscores the reliability of the study’s findings and emphasizes the effectiveness of RC wall construction in mitigating seismic risks and protecting life and property.

Probabilistic seismic performance assessment of aqueduct structures considering different sources of uncertainty

This investigation aims to propose the compound intensity measure and establish the seismic performance assessment framework considering multiple uncertainties for aqueduct structures. For this purpose, taking the typical three-span aqueduct structure as an engineering case, the uncertainty sample pairs are generated by Latin Hypercube Sampling. The seismic response under different ground motion intensities is obtained by incremental dynamic analysis (IDA), and the mapping relationship between structural damage characteristics and limit states is clarified. According to statistical analysis, quantitative recommendation values for the record-to-record, design parameters, performance index values, limit states and finite element model fidelity uncertainties are determined. Then, the multivariate compound intensity measure IMC is developed by taking into account the correlation between single intensity measure. Furthermore, the seismic performance assessment framework of aqueduct structures is established by the single and compound intensity measures. The total dispersion by multiple uncertainty factors is determined by the square-root-sum-of-squares (SRSS) method and the effects of uncertainty factors on the seismic fragility analysis results of aqueduct structures is explored. Subsequently, based on the seismic fragility function and the seismic hazard function, the seismic risk assessment method considering multiple uncertainties is proposed. The analysis results show that with the increase of uncertainty factors, the seismic fragility curves of the aqueduct structure under different limit states rotate clockwise along the IMR. The 50-year exceedance probabilities considering multiple uncertainties is 2.57∼3.14 (PGV) and 1.92∼2.28 (IMC) times that of considering only record-to-record and structural design parameters, further revealing the traditional method can overestimate the potential seismic risk of aqueduct structures. On the other hand, compared with the IMC, the effect of uncertainty factors on the 50-year exceedance probabilities obtained by PGV is more significant. In a word, the compound intensity measure and the multiple uncertainty analysis method proposed in this investigation can be utilized for the seismic performance assessment system of aqueduct structures.

Safety and Efficacy of Ashwagandha Root Extract on Cognition, Energy and Mood Problems in Adults: Prospective, Randomized, Placebo-Controlled Study.

This prospective, randomized, placebo-controlled study assessed the effects of Ashwagandha root extract (ARE) on cognition, energy, and mood in adults with self-reported cognitive and energy problems. Healthy subjects aged 30-75 years were randomized to receive ashwagandha (Withania somnifera) root extract (ARE) 600 mg/day (n = 60)/identical placebo (n = 60) orally for 8 weeks. Cognitive function was assessed at baseline and week 8 using a Computerized Mental Performance Assessment System (COMPASS). Secondary outcomes were Profile of Mood States Abbreviated Version (POMS-A), Mental Fatigue Scale (MFS) and Behavior Rating Inventory of Executive Function-Adult (BRIEF-A) for effects on mood, mental fatigue and executive function, respectively, assessed at baseline, week 4 and 8. Greater improvement (p < .05) from baseline scores were seen with ARE as against placebo for COMPASS items episodic memory, working memory and accuracy of attention. ARE also improved the POMS-A, MFS and BRIEF-A scores from baseline suggesting an improvement in mood, vigor, and an increase in the executive functioning respectively with ARE. The herb was well tolerated and had a good patient compliance with no serious adverse events reported in either of the groups. This study suggests that a dose of 600 mg a day can improve cognition, energy, and mood in adults with self-reported cognitive and energy problems.

A health system assessment approach to analysis of political parties' health proposals, Portugal.

Comparing health policy measures before elections and identifying potential gaps in the health policy debate can be challenging. We explored the use of the Health System Performance Assessment for Universal Health Coverage framework to analyse health policy proposals by classifying health policy measures outlined in political manifestos into four health system functions: governance, financing, resource generation and service delivery. As a case study, we analysed the political manifestos of all Portuguese parties with parliamentary representation ahead of the election in March 2024. We calculated the share of measures per health system function for individual political manifestos and identified potential gaps in the health policy debate. When required, we used additional classification criteria and local expertise on political and institutional knowledge. A snap general election was announced in Portugal in November2023, following an alleged corruption scandal, and political parties began publishing their manifestos on their websites in January2024. We identified and classified 350 health-related measures across the four functions: governance, 29.7% (104 measures); financing, 16.9% (59 measures); resource generation, 33.4% (117 measures); and service delivery, 20.0% (70 measures). These findings enabled characterization of the priorities of parties, facilitated cross-party comparisons and identified missing topics in the political debate. We show that the framework can be adapted to analyse political manifestos, providing a systematic method for comparing and synthesizing health policy proposals. We further demonstrate the potential for extending the framework's applicability beyond health system performance assessment, opening new avenues for policy analysis.

Thermal performance analysis of a domestic-size absorption cooling system incorporating nanofluid with thermal insulation in hot climate of Algeria

The increased demand for energy consumption for air conditioning, due to rising temperatures, has created challenges related to thermal comfort in residential environments .In the present study, a simulation of an air conditioning system for a small building was conducted, considering various absorption cooling scenarios to assess system performance through dynamic and economic analysis. The proposed system employs a parabolic trough collector in conjunction with a storage tank, designed to cool a 12 m² room in Adrar, Algeria. The study aims to identify the optimal scenario based on temperature, heat, and system coefficient of performance indicators. A computer program was developed using characteristic equations and finite difference methods to analyze the system's behavior with different nanofluid concentrations and thermal insulation. Simulation results show that scenario with nanofluid and insulation the best performance is achieved with a 4% nanofluid concentration, a 9 m² solar collector, a 0.3 m³ storage tank, and 0.05 m thick polystyrene insulation. The system can operate for 9 h, maintaining an indoor temperature of 27°C with a peak cooling load of 3 kW. The economic analysis estimates an investment cost of 4535.4$ and Net Present Value 3,370.40$ with a payback period of 12 years and 3 months.

6.Y.1. Defining, measuring, and reducing low-value care in Europe - proposing a new definition and framework

Abstract The EU Expert Group on Health Systems Performance Assessment (HSPA) selected value-based healthcare, with a focus on low-value care, as the work topic for 2023-2024. Against the backdrop of increasing healthcare expenditures and the overall aim to deliver high quality and efficient healthcare, efforts to reduce waste and inefficiencies have long been emerging in health systems worldwide. Value-based healthcare shifts the focus towards improving patient outcomes; the concept of low-value care in particular aims to identify health services that provide little or no health benefits but expose patients to potential harm. The COVID-19 pandemic clearly demonstrated that value-based healthcare is a prerequisite for high-performing health systems and the need to steer resource allocation to those services that maintain or improve health. The reduction in certain elective services observed during the pandemic (e.g. tonsillectomies) indicates that there may be areas for potential dis-investment and reallocation of resources to higher-value care. The pandemic has thereby emphasized the need for identifying and systematizing measurable efforts directed at reducing low-value care. Tackling low-value care can contribute to alleviating health workforce constraints by ensuring that efforts are focused where they are most beneficial, and not on unnecessary services. Engaging and educating the health workforce about low-value care and how to reduce it is a key measure in this direction. What is more, there is increasing awareness about the health sector’s considerable environmental footprint. Reducing low-value care would contribute to less greenhouse gas emissions, energy consumption and air pollution from the delivery of health services. Despite intensified efforts to address waste and inefficiencies in healthcare in the last decade, the ability of health systems in Europe to identify and reduce low-value care varies. Through the Expert Group’s work, a new comprehensive definition was proposed and a framework to distinguish different types of low-value care was developed as a basis for identifying and tackling low-value care in EU Member States. Indicators to measure low-value care as well as measures to reduce it were collected. This workshop aims to present the findings of the Expert Group´s work on low-value care and to discuss them with conference participants to both raise awareness and identify priority elements for future activities. After a brief introduction on the definition, framework, obstacles and solutions, the panelists will share their views and experiences, followed by a facilitated discussion with the audience. Key messages • A comprehensive definition of low-value care and an accompanying framework for categorizing and identifying low-value care is proposed. • Country experiences with indicators to measure low-value care and strategies to reduce it, as well as related methodological obstacles, offer substantial opportunities for cross-country learning.

7.H. Round table: Advancing societal goals through health systems: Insights from the Renewed HSPA Framework

Abstract The purpose of this workshop, entitled ‘Advancing societal goals through health systems: Insights from the renewed HSPA framework,’ is to take a deeper look at the intricate relationships between health systems and broader societal objectives. We will dissect the contributions of health systems to societal well-being, a concept that stretches beyond mere economic growth to include social cohesion, environmental sustainability, and economic development. The session will examine the renewed global Health System Performance Assessment Framework, which serves as a tool for policymakers to better understand how health systems fit together and explains how they perform. This framework allows for a clearer interpretation of health data and provides a pathway to pinpoint health system issues and design that are most likely to enhance performance and resilience. The workshop will delve into the three dimensions of societal well-being-social cohesion, economic development, and environmental sustainability-nested within the HSPA framework. We will explore the health system’s role in advancing these dimensions, such as fostering community bonds, supporting economic growth through a healthy workforce, and contributing to the sustainable management of environmental resources. Integrating health system performance into societal goals is a practical obligation to create a resilient, cohesive, and economically robust society. This workshop will engage stakeholders in a discourse to translate this integration into multisectoral and actionable policies, aligning health system goals with societal aspirations for a sustainable future. This workshop will focus on: How health system assessments can capture contributions to societal goals, underpinning sustainable economic and environmental practices. Real-world case studies showcasing health systems’ role in fostering societal well-being and advancing public health policies. Interactive discussions will shed light on how health systems can be pivotal in achieving the Sustainable Development Goals, particularly in the face of modern challenges such as climate change, demographic shifts, and economic pressures. Key messages • Health systems play a pivotal role in advancing societal well-being beyond traditional health outcomes. • The renewed HSPA framework is a robust tool for policymakers to align health system performance with broader societal goals. Speakers/Panelists Scott Greer University of Michigan, European Observatory on Health Systems and Policies, Ann Arbor, USA Andrea Schmidt Austrian Public Health Institute, Vienna, Austria

The WHO health system performance assessment applied to child healthcare in Luxembourg, 2011-2022

Abstract Background Health System Performance Assessments (HSPAs) evaluate health systems in terms of their objectives and their overall goals, such as access to quality services and health improvement. Beyond the overall health system assessment, HSPA can evaluate performance in providing care to specific populations. We assessed the response of the Luxembourg health system to children’s particular health needs, by populating the WHO HSPA framework for universal healthcare with child-specific indicators. Methods We searched international databases, guidelines, policy documents, and the scientific literature to identify child-specific indicators suitable for assessing the health system objectives as defined by the WHO HSPA framework. To select the most relevant indicators, we conducted expert appraisal regarding feasibility, validity and actionability. Those indicators were calculated based on available national data. To explore inequities within the system, we performed socioeconomic stratifications. Results Twenty-nine indicators were used to populate the framework, sourced from social security databases (n = 15), monitoring and surveillance (n = 11), and surveys (n = 2). For effectiveness assessment, we used 11 indicators and found that preventive services performed best for children under two years. Five indicators showed good accessibility to primary and secondary care. Another five indicators assessed safety indicating a recent increase in the relative use of broad-spectrum antimicrobials and an overuse of caesarean sections. Additional disaggregation of three indicators didn’t expose socioeconomic inequities in service delivery. Data gaps exist to assess children’s user-experience and financing of child health services. Conclusions The WHO HSPA framework proved valuable for evaluating the Luxembourg health system’s performance for children. We identified good performance in accessibility and effectiveness for young children, alongside data gaps to assess user-experience. Key messages • The application of national child-specific indicators to the WHO health system performance assessment, highlighted strengths in accessibility and effectiveness while also pointing to key data gaps. • We used the WHO health system performance assessment (HSPA) to evaluate the health system for children in Luxembourg. This exercise enhances the development of a tailored national HSPA framework.

Defining, measuring, and reducing low-value care – proposing a new comprehensive definition and framework

Abstract Despite intensified efforts to address waste and inefficiencies in healthcare in the last decade, the ability of health systems in Europe to identify and reduce low-value care varies. Through the EU Expert Group on Health System Performance Assessment’s work, a new comprehensive definition was proposed and a framework to distinguish different types of low-value care was developed as a basis for identifying and tackling low-value care in EU Member States. Indicators to measure low-value care as well as measures to reduce it were collected. This presentation will provide a brief introduction on the definition, framework, obstacles and solutions for reducing the use of low-value care in Europe. Speakers/Panelists Reinhard Busse Berlin University of Technology, Berlin, Germany Isabel de La Mata DG SANTE, European Commission, Luxembourg, Luxembourg Pacal Meeus Institut National d’assurance Maladie-Invalidité, Brussels, Belgium Ingrid Schmidt National Board of Health and Welfare, Sweden

Performance -based management system in hospital emergency

Background: Given the emphasis on evidence -based management in recent years and one of the new management methods is performance -based management, the purpose of this study was to establish an initial performance -based management system in the emergency department of Nikan Hospital in Tehran. Methods: Establishment of a science -based management system in the Nikan Hospital Emergency System includes six steps: 1) Determining the mission and goals of the organization, 2) Integrated Performance Assessment System 3) Response to Function, 4) Collection of Performance Data, 5) Data analysis, analysis, and performance data, 6) use of performance information to improve the organization. Results: Delays in the provision of bars, photography, experiments and specialized consultations in the crowded hours of emergency (20 to 24). The satisfaction of the patients was less than the service during emergency background (14 to 20). 70% of the patients declared recovery and about 70% announced that they would go to the hospital next time. Conclusion: Implementation of performance -based management system in the country's hospitals that lack the necessary infrastructure should pay many attentions and time and energy in this regard.

Integration of Moving Bed Biofilm Reactor (MBBR) and algal PhotoBioReactors (aPBR) for achieving carbon neutrality in wastewater treatment

Carbon neutrality is a primary goal for wastewater treatment plants (WWTPs), as they are responsible for significant greenhouse gas (GHG) emissions as well as unpleasant odour emissions.The paper shows a new modular biotechnology that enables simultaneous treatment of gaseous emissions and biofixation of CO2.A comparative assessment of system performances in removing target pollutants (toluene, p-xylene and hydrogen sulphide) was implemented. Results showed that the highest removal efficiency (RE) was recorded for the toluene, equaling 99.9 ± 0.1 %, for an inlet load (IL) of 9.91 ± 3.44 g m−3 d−1. During the experimental tests regarding hydrogen sulphide removal, the system recorded the highest CO2 assimilation, equal to −3.03 ± 0.93 g m−3 d−1. However, this assimilation rate did not correspond to the maximum volumetric biomass productivity (MVBP), equal to 1.3 g L−1 d−1, recorded with toluene treatment, with a maximum lipid productivity (MLP) of 450 mg L−1 d−1.The results demonstrated the complete adaptability of the investigated system, which can help to fill the gaps in the current technological landscape, providing an innovative biotechnology that can be directly implemented and environmentally sustainable.

Operational reliability and non-deterministic resilience estimation of active distribution network incorporating effect of real-time dynamic hosting capacity

Active distribution networks are increasingly recognized essential for achieving sustainable development goals. Traditionally, hosting capacity was considered as a static measure for planning distributed energy resources integration. This work introduces the concept of dynamic hosting capacity, which recurrently re-evaluates hosting capacity in response to erratic modern grid conditions. The introduction of dynamic hosting capacity facilitated testing variations of power injection from minimum to 100 %, sustaining power system governing parameter limits. This embarked the need of operational reliability assessment and enhancing situational awareness for optimum power injection and balance. To achieve operational reliability analysis based on dynamic hosting capacity, hybrid probability distribution function-based Monte Carlo simulation is proposed. This resulted in 85–90 %. improvisation of solar photovoltaic generation and load alignment, as this methodology provides comprehensive and accurate assessment of system performance under diverse uncertainties. The framework's validation includes projection of time-varying operational reliability indices, over time independent reliability indices i.e., dynamic loss of load probability, dynamic loss of load expectation, dynamic loss of load duration, dynamic loss of load frequency, dynamic grid margin, and dynamic grid dependency. This resulted in 30 % improvement in assessment of grid margin, facilitating reliable uncertainty handling competence. Additionally, expectation maximization algorithm is proposed to evaluate non-deterministic resilience due to ambiguities associated with solar photovoltaic distributed energy resources. The non-deterministic resilience assessment testified 80 % bounce-back rate, demonstrating better adaptability and robustness. The entire analysis is conducted in MATLAB, validated using Typhoon Hardware-in-Loop real-time platform, and compared with existing literatures to demonstrate its effectiveness.

Solo music performance assessment criteria: a systematic review.

Assessment is a crucial aspect of music performance. In pedagogical contexts, an effective assessment process can measure student achievement and inform instructional decisions that contribute to improving teaching and learning. However, music performance assessment is particularly challenging due to its inherent subjectivity, involving personal expression and interpretation, which can lead to divergent opinions. In this PRISMA systematic review (registration DOI: 10.17605/OSF.IO/CSM8Q), we aimed to delimit and analyze solo music performance assessment systems found in the literature to date, including their corresponding evaluation categories and descriptive criteria, rating methodology, and target audience. A search in three main scientific databases (Web of Science, Scopus, ERIC) was conducted using keywords associated with the topic of assessment in the field of solo music performance. Ultimately, 20 papers were selected and examined, resulting in 26 original assessment systems for analysis. Regarding sample characteristics, we found that studies mainly focused on evaluating high school and university students, with music teachers and faculty members serving as primary evaluators. Many assessment systems were designed to be applicable across various instruments, although some were tailored to specific instruments (e.g., piano, voice) and families (e.g., brass, woodwind). Systems typically structured evaluation around technical, interpretative/expressive, and various musical feature categories (e.g., pitch, rhythm, intonation), further elaborated with descriptive items. While five-point Likert scales were commonly used, recent studies indicated a shift towards rubrics for detailed feedback, which aids examiners' understanding and supports student progress. No differentiation was found in assessment criteria based on students' learning stages, suggesting an area for improvement in refining these assessment methods. This study identifies gaps and proposes improvements in existing assessment systems, providing a foundation for educators and policymakers to enhance curriculum design and instructional practices in music education.

Multiplexed Piezoelectric Electronic Skin with Haptic Feedback for Upper Limb Prosthesis

AbstractUpper limb amputation severely impairs tactile perception, limiting daily activities. Developing a near‐natural replacement with prosthetic devices requires improving user sensory experiences during object interactions. The ideal upper limb prosthesis should provide real‐time sensory feedback, mirroring natural experiences. Current prostheses struggle with providing adequate tactile feedback due to sensory limitations. Inspired by the sensory properties of skin, we present a micro‐fabricated, multiplexed electronic skin (e‐skin) with actuators for sensory feedback in upper limb amputation. The piezoelectric‐capacitive sensor array detects static pressure, temperature, vibration, and texture, with integrated actuators stimulating the skin to provide real‐time feedback. The sensors integrate with actuators via readout electronics, making the system standalone and easy to use. The flexible, compact sensor array design (two pixels within a 1 cm² footprint) detects a wide range of pressure (0.5–10 kPa), temperature (22–60 °C), vibration (35–100 Hz), and texture (2.5–45 Hz), suitable for daily use. The e‐skin, attached to a prosthetic finger, is tested for feasibility on human volunteers with wrist‐mounted actuators. Statistics are used to quantitatively assess system performance. The integration of multiplexed sensors and actuators enhances tactile feedback, improving the quality of life for people with upper limb amputations.