Monipar: movement data collection tool to monitor motor symptoms in Parkinson's disease using smartwatches and smartphones.

Introduction: Parkinson's disease (PD) is a neurodegenerative disorder commonly characterized by motor impairments. The development of mobile health (m-health) technologies, such as wearable and smart devices, presents an opportunity for the implementation of clinical tools that can support tasks such as early diagnosis and objective quantification of symptoms. Objective: This study evaluates a framework to monitor motor symptoms of PD patients based on the performance of standardized exercises such as those performed during clinic evaluation. To implement this framework, an m-health tool named Monipar was developed that uses off-the-shelf smart devices. Methods: An experimental protocol was conducted with the participation of 21 early-stage PD patients and 7 healthy controls who used Monipar installed in off-the-shelf smartwatches and smartphones. Movement data collected using the built-in acceleration sensors were used to extract relevant digital indicators (features). These indicators were then compared with clinical evaluations performed using the MDS-UPDRS scale. Results: The results showed moderate to strong (significant) correlations between the clinical evaluations (MDS-UPDRS scale) and features extracted from the movement data used to assess resting tremor (i.e., the standard deviation of the time series: r = 0.772, p < 0.001) and data from the pronation and supination movements (i.e., power in the band of 1-4 Hz: r = -0.662, p < 0.001). Conclusion: These results suggest that the proposed framework could be used as a complementary tool for the evaluation of motor symptoms in early-stage PD patients, providing a feasible and cost-effective solution for remote and ambulatory monitoring of specific motor symptoms such as resting tremor or bradykinesia.

Investigating Imperfect Cloning for Extending Quantum Communication Capabilities.

Quantum computing allows the implementation of powerful algorithms with enormous computing capabilities and promises a secure quantum Internet. Despite the advantages brought by quantum communication, certain communication paradigms are impossible or cannot be completely implemented due to the no-cloning theorem. Qubit retransmission for reliable communications and point-to-multipoint quantum communication (QP2MP) are among them. In this paper, we investigate whether a Universal Quantum Copying Machine (UQCM) generating imperfect copies of qubits can help. Specifically, we propose the Quantum Automatic Repeat Request (QARQ) protocol, which is based on its classical variant, as well as to perform QP2MP communication using imperfect clones. Note that the availability of these protocols might foster the development of new distributed quantum computing applications. As current quantum devices are noisy and they decohere qubits, we analyze these two protocols under the presence of various sources of noise. Three major quantum technologies are studied for these protocols: direct transmission (DT), teleportation (TP), and telecloning (TC). The Nitrogen-Vacancy (NV) center platform is used to create simulation models. Results show that TC outperforms TP and DT in terms of fidelity in both QARQ and QP2MP, although it is the most complex one in terms of quantum cost. A numerical study shows that the QARQ protocol significantly improves qubit recovery and that creating more clones does not always improve qubit recovery.

Supporting Heterogenous Traffic on Top of Point-to-Multipoint Light-Trees.

New 5 G and beyond services demand innovative solutions in optical transport to increase efficiency and flexibility and reduce capital (CAPEX) and operational (OPEX) expenditures to support heterogeneous and dynamic traffic. In this context, optical point-to-multipoint (P2MP) connectivity is seen as an alternative to provide connectivity to multiple sites from a single source, thus potentially both reducing CAPEX and OPEX. Digital subcarrier multiplexing (DSCM) has been shown as a feasible candidate for optical P2MP in view of its ability to generate multiple subcarriers (SC) in the frequency domain that can be used to serve several destinations. This paper proposes a different technology, named optical constellation slicing (OCS), that enables a source to communicate with multiple destinations by focusing on the time domain. OCS is described in detail and compared to DSCM by simulation, where the results show that both OCS and DSCM provide a good performance in terms of the bit error rate (BER) for access/metro applications. An exhaustive quantitative study is afterwards carried out to compare OCS and DSCM considering its support to dynamic packet layer P2P traffic only and mixed P2P and P2MP traffic; throughput, efficiency, and cost are used here as the metrics. As a baseline for comparison, the traditional optical P2P solution is also considered in this study. Numerical results show that OCS and DSCM provide a better efficiency and cost savings than traditional optical P2P connectivity. For P2P only traffic, OCS and DSCM are utmost 14.6% more efficient than the traditional lightpath solution, whereas for heterogeneous P2P + P2MP traffic, a 25% efficiency improvement is achieved, making OCS 12% more efficient than DSCM. Interestingly, the results show that for P2P only traffic, DSCM provides more savings of up to 12% than OCS, whereas for heterogeneous traffic, OCS can save up to 24.6% more than DSCM.

Accurate Low Complex Modulation Format and Symbol Rate Identification for Autonomous Lightpath Operation.

Network automation promises to reduce costs while guaranteeing the required performance; this is paramount when dealing with the forecasted highly dynamic traffic that will be generated by new 5G/6G applications. In optical networks, autonomous lightpath operation entails that the optical receiver can identify the configuration of a received optical signal without necessarily being configured from the network controller. This provides relief for the network controller from real-time operation, and it can simplify the operation in multi-domain scenarios, where an optical connection spans across more than one domain. Consequently, in this work, we propose a blind and low complex modulation format (MF) and symbol rate (SR) identification algorithm. The algorithm is based on studying the effects of decoding an optical signal with different MFs and SRs. Extensive MATLAB-based simulations have been carried out which consider a coherent wavelength division multiplexed system based on 32 and 64 quadrature amplitude modulated signals at up to 96 GBd, thus enabling bit rates of up to 800 Gb/s/channel. The results show remarkable identification accuracy in the presence of linear and nonlinear noise for a wide range of feasible configurations.

Ergonomic assessment of postal workers' pain symptoms and musculoskeletal risks related to parcel processing activity for delivery.

The parcel delivery activity is carried out all over the world and workers in this sector have suffered from musculoskeletal disorders (MSDs) due to the strong demand for work generated by the recent increase in e-commerce. This study aimed to evaluate postal workers' pain symptoms, movements and identify MSDs risks related to the parcel processing activity for delivery, proposing preventive measures. A sample of thirty-two workers was evaluated with the application of sociodemographic and Nordic questionnaires and electrical bioimpedance. The motion capture sensors were used to evaluate right/left shoulder joints, segment C7-T1 (Cervical) and segment L5-S1 (Lumbar) of three postal workers (percentiles of anthropometric data: 5, 50, and 95) during four real work activities that are part of the parcel processing. The analyzed workers presented musculoskeletal complaints in practically all body regions, with a greater prevalence in shoulders, hands, lower back, and knees. According to the Body Mass Index (BMI), they were on average overweight (27.8 ± 3.7 kg/m2). In the movement analysis, we identified risks related to cervical protrusion, anterior trunk flexion, and shoulder flexion, in addition to repetitive movements. In some activities, the higher stature showed an increase in lumbar and cervical anterior flexion. The set of evaluations showed that the activity of processing orders for delivery offers musculoskeletal risks. We identify that ergonomic adaptations are necessary to adapt the heights of the work environment to the statures of the postal workers. Relevance to industry: The activity of processing orders for delivery is carried out practically all over the world generating jobs and income for its employees. Nonetheless, there are still situations of ergonomic disadvantage that can generate musculoskeletal risks. The findings elucidate ergonomic risks and provide useful information for future ergonomic interventions in the postal/delivery workplace environment.

Reopening higher education buildings in post-epidemic COVID-19 scenario: monitoring and assessment of indoor environmental quality after implementing ventilation protocols in Spain and Portugal.

Post-epidemic protocols have been implemented in public buildings to keep indoor environments safe. However, indoor environmental conditions are affected by this decision, which also affect the occupants of buildings. This fact has major implications in educational buildings, where the satisfaction and learning performance of students may also be affected. This study investigates the impact of post-epidemic protocols on indoor environmental conditions in higher education buildings of one Portuguese and one Spanish university. A sensor monitoring campaign combined with a simultaneous questionnaire was conducted during the reopening of the educational buildings. Results showed that although renewal air protocols were effective and the mean CO2 concentration levels remained low (742 ppm and 519 ppm in Portugal and Spain universities, respectively), students were dissatisfied with the current indoor environmental conditions. Significant differences were also found between the responses of Portuguese and Spanish students. Indeed, Spanish students showed warmer preferences (thermal neutrality = 23.3℃) than Portuguese students (thermal neutrality = 20.7℃). In terms of involved indoor factors, the obtained data showed significant correlations (p < 0.001) between acoustic factors and overall satisfaction in the Portuguese students (ρ = 0.540) and between thermal factors and overall satisfaction in the Spanish students (ρ = 0.522). Therefore, indoor environmental conditions should be improved by keeping spaces safe while minimizing the impact of post-epidemic protocols on student learning performance.

Automatic Resting Tremor Assessment in Parkinson's Disease Using Smartwatches and Multitask Convolutional Neural Networks.

Resting tremor in Parkinson's disease (PD) is one of the most distinctive motor symptoms. Appropriate symptom monitoring can help to improve management and medical treatments and improve the patients' quality of life. Currently, tremor is evaluated by physical examinations during clinical appointments; however, this method could be subjective and does not represent the full spectrum of the symptom in the patients' daily lives. In recent years, sensor-based systems have been used to obtain objective information about the disease. However, most of these systems require the use of multiple devices, which makes it difficult to use them in an ambulatory setting. This paper presents a novel approach to evaluate the amplitude and constancy of resting tremor using triaxial accelerometers from consumer smartwatches and multitask classification models. These approaches are used to develop a system for an automated and accurate symptom assessment without interfering with the patients' daily lives. Results show a high agreement between the amplitude and constancy measurements obtained from the smartwatch in comparison with those obtained in a clinical assessment. This indicates that consumer smartwatches in combination with multitask convolutional neural networks are suitable for providing accurate and relevant information about tremor in patients in the early stages of the disease, which can contribute to the improvement of PD clinical evaluation, early detection of the disease, and continuous monitoring.

Ergonomic intervention on a packing workstation with robotic aid -case study at a furniture manufacturing industry.

BACKGROUND: Several risk factors among packing lines workers can lead to Work-related Musculoskeletal Disorders (WRMSD) occurrence. Foreseeing WRMSD prevention and productivity increase, some furniture manufacturing industries have been investing in the adoption of robotic solutions. In this field, ergonomics plays an important role to verify if automation implementation has been successful. OBJECTIVE: This study aims to address the general impact and effectiveness from an ergonomics point of view of the implementation of a robotic aid in a packing workstation. METHODS: The Nordic Musculoskeletal Questionnaire (NMQ) was applied to 14 workers of semi-automated packing lines. Some additional questions about occupational conditions were included. In order to assess the ergonomic impact of the robotic aid, Rapid Upper Limb Assessment (RULA) was also applied by trained ergonomists, by analyzing the considered packing workstations before and after the adoption of the robotic aid proposed solution. RESULTS: The results showed that trunk torsion was the most highlighted WRMSD risk factor by all workers, associating it with the lumbar pain. The obtained RULA scores demonstrated that the adoption of a robotic aid eliminated this risk factor and, consequently, reduced the corresponding WRMSD risk. CONCLUSIONS: The adoption of robotic aids can be instrumental in reducing WRMSD risk in furniture manufacturing industries. Ergonomic studies with workers' participatory approaches seem to be an appropriate strategy to enable the validation and development of industrial robotic solutions.

Deep Learning Approaches for Detecting Freezing of Gait in Parkinson's Disease Patients through On-Body Acceleration Sensors.

Freezing of gait (FOG) is one of the most incapacitating motor symptoms in Parkinson's disease (PD). The occurrence of FOG reduces the patients' quality of live and leads to falls. FOG assessment has usually been made through questionnaires, however, this method can be subjective and could not provide an accurate representation of the severity of this symptom. The use of sensor-based systems can provide accurate and objective information to track the symptoms' evolution to optimize PD management and treatments. Several authors have proposed specific methods based on wearables and the analysis of inertial signals to detect FOG in laboratory conditions, however, its performance is usually lower when being used at patients' homes. This study presents a new approach based on a recurrent neural network (RNN) and a single waist-worn triaxial accelerometer to enhance the FOG detection performance to be used in real home-environments. Also, several machine and deep learning approaches for FOG detection are evaluated using a leave-one-subject-out (LOSO) cross-validation. Results show that modeling spectral information of adjacent windows through an RNN can bring a significant improvement in the performance of FOG detection without increasing the length of the analysis window (required to using it as a cue-system).

Voice-Based Classification of Amyotrophic Lateral Sclerosis: Where Are We and Where Are We Going? A Systematic Review.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal progressive motor neuron disease. People with ALS demonstrate various speech problems. SUMMARY: We aim to provide an overview of studies concerning the diagnosis of ALS based on the analysis of voice samples. The main focus is on the feasibility of the use of voice and speech assessment as an effective method to diagnose the disease, either in clinical or pre-clinical conditions, and to monitor the disease progression. Specifically, we aim to examine current knowledge on: (a) voice parameters and the data models that can, most effectively, provide robust results; (b) the feasibility of a semi-automatic or automatic diagnosis and outcomes; and (c) the factors that can improve or restrict the use of such systems in a real-world context. Key Messages: The studies already carried out on the possibility of diagnosis of ALS using the voice signal are still sparse but all point to the importance, feasibility and simplicity of this approach. Most cohorts are small which limits the statistical relevance and makes it difficult to infer broader conclusions. The set of features used, although diverse, is quite circumscribed. ALS is difficult to diagnose early because it may mimic several other neurological diseases. Promising results were found for the automatic detection of ALS from speech samples and this can be a feasible process even in pre-symptomatic stages. Improved guidelines must be set in order to establish a robust decision model.

Occupational Risk Prevention through Smartwatches: Precision and Uncertainty Effects of the Built-In Accelerometer.

Wearable technology has had a significant growth in the last years; this is particularly true of smartwatches, due to their potential advantages and ease of use. These smart devices integrate sensors that can be potentially used within industrial settings and for several applications, such as safety, monitoring, and the identification of occupational risks. The accelerometer is one of the main sensors integrated into these devices. However, several studies have identified that sensors integrated into smart devices may present inaccuracies during data acquisition, which may influence the performance of their potential applications. This article presents an analysis from the metrological point of view to characterize the amplitude and frequency response of the integrated accelerometers in three currently available commercial smartwatches, and it also includes an analysis of the uncertainties associated with these measurements by adapting the procedures described in several International Organization for Standardization (ISO) standards. The results show that despite the technical limitations produced by the factory configuration, these devices can be used in various applications related to occupational risk assessment. Opportunities for improvement have also been identified, which will allow us to take advantage of this technology in several innovative applications within industrial settings and, in particular, for occupational health purposes.

Resultados de um programa de tratamento, com ou sem treinamento físico, em crianças com asma / Results of a management program with or without physical training in children with asthma

Estudamos prospectivamente a resistência aeróbia em 41 crianças (23 do sexo masculino, idades: 7 a 9 anos) com asma estável, leve ou moderada, utilizando o teste corrida-caminhada, em avaliaçoes trimestrais por 12 meses. Dois grupos foram constituídos aleatoriamente, o grupo controle, sem treinamento (ST, 11 meninos e 8 meninas) e o grupo com treinamento (CT, 12 meninos e 10 meninas). O treinamento consistiu em um período breve de aquecimento, exercícios respiratórios e atividades aeróbias perfazendo 60 minutos, duas vezes por semana. No início do estudo, os grupos eram homogêneos quanto à idade, sexo, medidas antropométricas e desempenho na prova de resistência aeróbia. Ao longo do estudo o grupo CT, em relaçao ao grupo ST, apresentou um aumento significante do desempenho físico, melhor adaptaçao cardiovascular ao exercício avaliado pela resposta da freqüência cardíaca e valores mais elevados dos parâmetros espirométricos obtidos antes e depois da prova aeróbia de` nove minutos (PFE) e antes e depois do teste ciclo-ergométrico (VEF, e FEFzs.7soo), principalmente no sexo feminino. No grupo CT houve menos episódios de BIE. As médias das distâncias percorridas (metros, m), em nove minutos, no início do estudo, com três, seis, nove e 1-2 meses pelo grupo ST, sexo masculino, foram: 1287, 1288, 1300, 1316, 1302 m e para o sexo feminino: 1120, 1092, 1085, 1110, 1162 m. As médias do grupo CT, sexo masculino, foram: 1261, 1364, 1412*, 1392*, 1460* m e para o sexo feminino: 1117, 1152, 1121, 1201 *, 1244* m (significantes (o) em relaçao aos valores iniciais de cada grupo). O número de dias em crise de asma foi significantemente menor no grupo CT, principalmente no sexo feminino e quanto ao número de dias em uso de medicaçao foi menor somente no sexo feminino do grupo CT Crianças com asma devem ter treinamento físico orientado como parte importante do conjunto das medidas terapêuticas

Avaliaçäo da condiçäo aeróbia em crianças com asma e controles, pelo teste corrida-caminhada (teste de Cooper) / Aerobic capacity evaluation in children with asthma using cooper test

Estudamos a capacidade aeróbica de 29 crianças, sendo 13 meninos, com asma leve ou moderada, com idades entre 10 e 12 anos, pelo teste corrida-caminhada (teste de Cooper). Os resultados das distâncias percorridas foram expressos em metros (m). Utilizamos o pico de fluxo expiratório (PFE) como parâmetro espirométrico para avaliar a funçao pulmonar antes e depois dos testes aeróbicos nos vários períodos de tempo considerados: no primeiro minuto (imediatamente após o término do teste), 5, 10, 15, 30 e 60 minutos. Constituíram o grupo-controle 45 crianças sadias, sendo 21 meninos. Os grupos controle e asmático eram homogêneos em termos de idade, peso, altura e avaliaçao espirométrica obtida antes dos testes de capacidade aeróbica realizados quando as crianças se encontravam sem sintomas de asma. A análise dos resultados mostrou que os valores das distâncias percorridas pelas crianças asmáticas foram significantemente menores do que os dos controles, independentemente do sexo. Os meninos do grupo-asmático percorreram, em méia, 1788 m versus 2086 m do grupo-controle, e as meninas do grupo-asmático percorreram, em média 1514 m versus 1841 m do grupo-controle. Independentemente do grupo a que pertenciam, os meninos obtiveram melhores resultados do que as meninas. A asma induzida por exercício (AIE) foi observada principalmente nos tempos: primeiro minuto (imediatamente após o exercício). 5 e 10 minutos após os testes de corrida. O quinto minuto foi o melhor momento para evidenciar o maior índice de positividade de AIE. O grupo-asmático teve prevalência de AIE de 89,6 por cento. Consideramos casos positivos de AIE quando ocorreu que da do PFE de pelo menos 10 por cento após o exercício, em relaçao aos valores basais. Este valor de 10 por cento de queda do PFE estava acima do ponto de corte (Cutoff point) indicado pela análise da curva ROC "Relative Operating Characteristic", que foi de 5 por cento. Nao houve discordância significante entre os dados obtidos pela história clínica e o teste de exercício aeróbio quanto à positividade de AIE. No grupo-controle nao houve ocorrência de AIE.