General Treatments Promoting Independent Living in Parkinson's Patients and Physical Therapy Approaches for Improving Gait-A Comprehensive Review.

This study delves into the multifaceted approaches to treating Parkinson's disease (PD), a neurodegenerative disorder primarily affecting motor function but also manifesting in a variety of symptoms that vary greatly among individuals. The complexity of PD symptoms necessitates a comprehensive treatment strategy that integrates surgical interventions, pharmacotherapy, and physical therapy to tailor to the unique needs of each patient. Surgical options, such as deep brain stimulation (DBS), have been pivotal for patients not responding adequately to medication, offering significant symptom relief. Pharmacotherapy remains a cornerstone of PD management, utilizing drugs like levodopa, dopamine agonists, and others to manage symptoms and, in some cases, slow down disease progression. However, these treatments often lead to complications over time, such as motor fluctuations and dyskinesias, highlighting the need for precise dosage adjustments and sometimes combination therapies to optimize patient outcomes. Physical therapy plays a critical role in addressing the motor symptoms of PD, including bradykinesia, muscle rigidity, tremors, postural instability, and akinesia. PT techniques are tailored to improve mobility, balance, strength, and overall quality of life. Strategies such as gait and balance training, strengthening exercises, stretching, and functional training are employed to mitigate symptoms and enhance functional independence. Specialized approaches like proprioceptive neuromuscular facilitation (PNF), the Bobath concept, and the use of assistive devices are also integral to the rehabilitation process, aimed at improving patients' ability to perform daily activities and reducing the risk of falls. Innovations in technology have introduced robotic-assisted gait training (RAGT) and other assistive devices, offering new possibilities for patient care. These tools provide targeted support and feedback, allowing for more intensive and personalized rehabilitation sessions. Despite these advancements, high costs and accessibility issues remain challenges that need addressing. The inclusion of exercise and activity beyond structured PT sessions is encouraged, with evidence suggesting that regular physical activity can have neuroprotective effects, potentially slowing disease progression. Activities such as treadmill walking, cycling, and aquatic exercises not only improve physical symptoms but also contribute to emotional well-being and social interactions. In conclusion, treating PD requires a holistic approach that combines medical, surgical, and therapeutic strategies. While there is no cure, the goal is to maximize patients' functional abilities and quality of life through personalized treatment plans. This integrated approach, along with ongoing research and development of new therapies, offers hope for improving the management of PD and the lives of those affected by this challenging disease.

A Comprehensive Review: Robot-Assisted Treatments for Gait Rehabilitation in Stroke Patients.

Robot-assisted gait training (RAGT) is at the cutting edge of stroke rehabilitation, offering a groundbreaking method to improve motor recovery and enhance the quality of life for stroke survivors. This review investigates the effectiveness and application of various RAGT systems, including both end-effector and exoskeleton robots, in facilitating gait enhancements. The selection process for this comprehensive analysis involved a meticulous review of the literature from databases such as PubMed, the Cochrane Library, and EMBASE, focusing on studies published between 2018 and 2023. Ultimately, 27 studies met the criteria and were included in the final analysis. The focus of these studies was on the various RAGT systems and their role in promoting gait and balance improvements. The results of these studies conclusively show that patients experience significant positive effects from RAGT, and when combined with other physiotherapy methods, the outcomes are notably superior in enhancing functional ambulation and motor skills. This review emphasizes RAGT's capability to deliver a more customized and effective rehabilitation experience, highlighting the importance of tailoring interventions to meet the specific needs of each patient.

Vibration, and temperature run-to-failure dataset of ball bearing for prognostics.

Condition based maintenance (CBM) has become a very important issue in the industry because it can decrease the inventory as the need of parts can be planned by the identification of a potential failure. However, in order to predict the life span of the ball bearing, it is necessary to acquire data according to the all life span of the bearing. This article presents the time-series dataset, including vibration, and temperature, of the ball bearing under run-to-failure. Through the accelerated life test, the ball bearing was failed at 128 working hours, and the vibration and temperature data for the all running section were included. The type of fault was identified through microscopic analysis of the damaged ball bearing. The established dataset can be used to verify newly developed state-of-the-art methods for prognosis the remaining useful life (RUL) of the ball bearing. Mendeley Data. DOI: 10.17632/5hcdd3tdvb.6.

Cardiovascular hardware simulator and artificial aorta-generated central blood pressure waveform database according to various vascular ages for cardiovascular health monitoring applications.

This study presents a database of central blood pressure waveforms according to cardiovascular health conditions, to supplement the lack of clinical data in cardiovascular health research, constructed by a cardiovascular simulator. Blood pressure (BP) is the most frequently measured biomarker, and in addition to systolic and diastolic pressure, its waveform represents the various conditions of cardiovascular health. A BP waveform is formed by overlapping the forward and reflected waves, which are affected by the pulse wave velocity (PWV). The increase in vascular stiffness with aging increases PWV, and the PWV-age distribution curve is called vascular age. For cardiovascular health research, extensive data of central BP waveform is essential, but the clinical data published so far are insufficient and imbalanced in quantity and quality. This study reproduces the central BP waveform using a cardiovascular hardware simulator and artificial aortas, which mimic the physiological structure and properties of the human. The simulator can adjust cardiovascular health conditions to the same level as humans, such as heart rate of 40-100 BPM, stroke volume of 40-100 mL, and peripheral resistance of 12 steps. Also, 6 artificial aortas with vascular ages in the 20-70 were fabricated to reproduce the increase in vascular stiffness due to aging. Vascular age calculated from measured stiffness of artificial aorta and central BP waveform showed an error of less than 3 years from the clinical value. Through this, a total of 636 waveforms were created to construct a central BP waveform database according to controlled various cardiovascular health conditions.

Reproduction of human blood pressure waveform using physiology-based cardiovascular simulator.

This study presents a cardiovascular simulator that mimics the human cardiovascular system's physiological structure and properties to reproduce the human blood pressure waveform. Systolic, diastolic blood pressures, and its waveform are key indicators of cardiovascular health. The blood pressure waveform is closely related to the pulse wave velocity and the overlap of the forward and reflected pressure waves. The presented cardiovascular simulator includes an artificial aorta made of biomimetic silicone. The artificial aorta has the same shape and stiffness as the human standard and is encased with a compliance chamber. The compliance chamber prevents distortion of the blood pressure waveform from strain-softening by applying extravascular pressure. The blood pressure waveform reproduced by the simulator has a pressure range of 80-120 mmHg, a pulse wave velocity of 6.58 m/s, and an augmentation index of 13.3%. These values are in the middle of the human standard range, and the reproduced blood pressure waveform is similar to that of humans. The errors from the human standard values are less than 1 mmHg for blood pressure, 0.05 m/s for pulse wave velocity, and 3% for augmentation index. The changes in blood pressure waveform according to cardiovascular parameters, including heart rate, stroke volume, and peripheral resistance, were evaluated. The same pressure ranges and trends as in humans were observed for systolic and diastolic blood pressures according to cardiovascular parameters.

Experimental characterization of a shape optimized acoustic lens: Application to compact speakerphone design.

This work presents the shape optimization and subsequent experimental validation of an acoustic lens with application to a compact loudspeaker, such as found in commercial speakerphones. The shape optimization framework is based on a combined lumped parameter and boundary element method model using free form deformation geometry parameterization. To test the optimized design, the loudspeaker lens is three-dimensionally printed and experimentally characterized under anechoic conditions on a finite baffle with respect to its off-axis frequency response. The overall tendencies of the frequency responses agree well between measurement and simulations within the optimization frequency range and at low frequencies. The optimization process is applied to a model including acoustic lumped parameter approximations. The shortcomings of the assumptions made in the model are revealed by laser Doppler vibrometer measurements of the loudspeaker driver and modelling of the mechanical vibrations of the lens.

Vibration, acoustic, temperature, and motor current dataset of rotating machine under varying operating conditions for fault diagnosis.

Rotating machines are often operated under various operating conditions. However, the characteristics of the data varies with their operating conditions. This article presents the time-series dataset, including vibration, acoustic, temperature, and driving current data of rotating machines under varying operating conditions. The dataset was acquired using four ceramic shear ICP based accelerometers, one microphone, two thermocouples, and three current transformer (CT) based on the international organization for standardization (ISO) standard. The conditions of the rotating machine consisted of normal, bearing faults (inner and outer races), shaft misalignment, and rotor unbalance with three different torque load conditions (0 Nm, 2 Nm, and 4 Nm). This article also reports the vibration and driving current dataset of a rolling element bearing under varying speed conditions (680 RPM to 2460 RPM). The established dataset can be used to verify newly developed state-of-the-art methods for fault diagnosis of rotating machines. Mendeley Data. DOI:10.17632/ztmf3m7h5x.6, DOI:10.17632/vxkj334rzv.7, DOI:10.17632/x3vhp8t6hg.7, DOI:10.17632/j8d8pfkvj2.7.

Vibration and current dataset of three-phase permanent magnet synchronous motors with stator faults.

Permanent magnet synchronous motors (PMSM) are widely used in industry applications such as home appliances, manufacturing process, high-speed trains, and electric vehicles. Unexpected faults of PMSM are directly related to the significant losses in the engineered systems. The majority of motor faults are bearing fault (mechanical) and stator fault (electrical). This article reports vibration and driving current dataset of three-phase PMSM with three different motor powers under eight different severities of stator fault. PMSM conditions including normal, inter-coil short circuit fault, and inter-turn short circuit fault in three motors are demonstrated with different powers of 1.0 kW, 1.5 kW and 3.0 kW, respectively. The PMSMs are operated under the same torque load condition and rotating speed. Dataset is acquired using one integrated electronics piezo-electric (IEPE) based accelerometer and three current transformers (CT) with National Instruments (NI) data acquisition (DAQ) board under international organization for standardization standard (ISO 10816-1:1995). Established dataset can be used to verify newly developed state-of-the-art methods for PMSM stator fault diagnosis. Mendeley Data. DOI: 10.17632/rgn5brrgrn.5.

Correlation analysis of human upper arm parameters to oscillometric signal in automatic blood pressure measurement.

Cardiovascular diseases are the leading cause of global deaths, making cardiovascular health monitoring important. Measuring blood pressure using an automatic sphygmomanometer is the most widely used method to monitor cardiovascular health due to its accessibility, convenience, and strong correlation with cardiovascular diseases. In this work, in order to estimate brachial artery diameter, stiffness, or thickness using an automatic sphygmomanometer, the correlation between upper arm parameters and the oscillometric signal was intensively investigated through analytical, numerical, and experimental approaches. The parametric studies commonly revealed that the inner radius of the brachial artery is the most influential parameter in determining the amplitude of the oscillometric signal. The experimental results of using a cardiovascular simulator (a virtual patient) combined with upper arm phantoms with various inner radii of the brachial artery showed a 6.5% change in the oscillometric signal amplitude with a 10% artery radius variation. It was concluded that the oscillometric signal can be used to evaluate brachial artery diameter. Based on the clinical relationship between brachial artery diameter and cardiovascular risk factors such as hypertension, diabetes, and obesity, this study showed and verified a novel method to monitor brachial artery diameter and hence, cardiovascular risks while measuring blood pressure.

Deep learning based cough detection camera using enhanced features.

Coughing is a typical symptom of COVID-19. To detect and localize coughing sounds remotely, a convolutional neural network (CNN) based deep learning model was developed in this work and integrated with a sound camera for the visualization of the cough sounds. The cough detection model is a binary classifier of which the input is a two second acoustic feature and the output is one of two inferences (Cough or Others). Data augmentation was performed on the collected audio files to alleviate class imbalance and reflect various background noises in practical environments. For effective featuring of the cough sound, conventional features such as spectrograms, mel-scaled spectrograms, and mel-frequency cepstral coefficients (MFCC) were reinforced by utilizing their velocity (V) and acceleration (A) maps in this work. VGGNet, GoogLeNet, and ResNet were simplified to binary classifiers, and were named V-net, G-net, and R-net, respectively. To find the best combination of features and networks, training was performed for a total of 39 cases and the performance was confirmed using the test F1 score. Finally, a test F1 score of 91.9% (test accuracy of 97.2%) was achieved from G-net with the MFCC-V-A feature (named Spectroflow), an acoustic feature effective for use in cough detection. The trained cough detection model was integrated with a sound camera (i.e., one that visualizes sound sources using a beamforming microphone array). In a pilot test, the cough detection camera detected coughing sounds with an F1 score of 90.0% (accuracy of 96.0%), and the cough location in the camera image was tracked in real time.

A Helmholtz resonator on elastic foundation for measurement of the elastic coefficient of human skin.

A new sensing mechanism is proposed for the measurement of elasticity of human skin by utilizing Helmholtz resonator with a flexible membrane mounted at the bottom and putting on an elastic foundation. Elastic coefficient of human skin is modeled as the elastic foundation modulus, based on the assumption that human skin is equivalent to the Winkler foundation. For the Helmholtz resonator, the acoustic transmission loss (by which resonant frequency can be acquired) was derived by using the receptance coupling method, based on the theories of conventional Helmholtz resonator and fixed-edge membrane on elastic foundation. The fundamental resonant frequency of the proposed Helmholtz resonator was proved to be related with the elastic foundation modulus, and was used as the indicator of elastic foundation modulus to be measured. Theoretical derivation for measuring elastic foundation modulus and analytical example were presented. Experiments measuring the elastic foundation modulus of the phantoms were carried out by utilizing phantoms with different stiffness using gelatin with corresponding different concentrations. The analytical and experimental results verified the effectiveness of the proposed method. Nanoindentation test was conducted for comparison, and relative errors ranged from 9.24% to 20.06% were obtained, which tends to be higher with the increasing concentration of gelatin.

Measurement of an Analyte Concentration in Test Solution by Using Helmholtz Resonator for Biosensor Applications.

In this paper, an indirect method of measuring an analyte concentration in a test solution using the resonant frequency change of a Helmholtz resonator is proposed, using a novel architecture of Helmholtz resonator filled with two kinds of fluids (fixed fluid and test solution). Since the analyte concentration yields changes of density and sound speed of the test solution, the resonant frequency of the proposed Helmholtz resonator is affected by the analyte concentration of the test solution. From this effect, the analyte concentration of the test solution can be measured by the spectrum of acoustic resonance of the Helmholtz resonator. The experiment was done using a 3D-printed Helmholtz resonator system with an acoustic power source and detectors, which is consistent with analytical results and showed that the analyte concentration can be measured with higher sensitivity compared to conventional cantilever-type sensors. As an example application, the possibility of measuring glucose concentration of human blood was demonstrated, showing higher sensitivity and relatively low frequency range compared to previous resonance based methods.

Electro-absorption modulator with an asymmetric coupled triple quantum well for low-voltage operation.

We present an electro-absorption modulator based on the enhanced electro-optic effect of an asymmetric coupled triple quantum well (ACTQW) to achieve a large transmittance difference at a low driving voltage for high-definition (HD) three-dimensional (3D) imaging applications. Our numerical calculations show that an ACTQW structure can provide a significantly lower-voltage operation without degrading the absorption coefficient change at the operating wavelength of 850 nm. The fabricated electro-absorption modulator (EAM) based on an ACTQW shows that the operating voltage can be reduced by nearly 50% compared with an EAM based on a conventional rectangular quantum well while also achieving a large transmittance difference in excess of 50%, which is in good agreement with the numerical calculation results. These results suggest that using an EAM with an ACTQW is a promising approach for the realization of a high-resolution 3D imaging system.

Coupled tandem cavities based electro-absorption modulator with asymmetric tandem quantum well for high modulation performance at low driving voltage.

We propose and demonstrate a new electro-absorption modulator (EAM) based on coupled tandem cavities (CTC) having asymmetric tandem quantum well (ATQW) structure with separated electrode configuration to achieve large transmittance change over a broad spectral range at low driving voltage for high definition (HD) 3D imaging applications. Our theoretical calculations show that CTC with ATQW structure can provide large transmittance change over a wide spectral range at low driving voltage. By introducing separated electrode configuration, the fabricated EAM having CTC with ATQW structure shows a large transmittance change over 50%, almost three times larger spectral bandwidth compared to that of EAM having single cavity with a single thickness quantum well without significantly increasing the applied voltage. In addition, the CTC with ATQW structure also shows high speed modulation up to 28 MHz for the device having a large area of 2 mm x 0.5 mm. This high transmittance change, large spectral bandwidth and low voltage operation over a large device area for the EAM having CTC with ATQW demonstrates their huge potential as an optical image modulator for HD 3D imaging applications.

Wide spectral bandwidth electro-absorption modulator using coupled micro-cavity with asymmetric tandem quantum well.

For reliable three dimensional (3D) imaging system, it is necessary for the optical shutter to have a wide spectral bandwidth operation and enhanced modulation depth. We propose an electro-absorption modulator (EAM) based on coupled Fabry-Perot cavities with micro-cavity (CCMC) which uses asymmetric tandem quantum wells (ATQWs) to obtain improved spectral bandwidth and enhanced modulation depth. Several modulator designs are investigated to obtain improved modulation performance such as wider spectral bandwidth and enhanced modulation depth. It was found that among all the studied modulator geometries, CCMC structure with ATQWs provides the widest spectral bandwidth of 9.6nm and high modulation depth in excess of 50% at -24V, which is good agreement with theoretical calculations. These results suggest that EAM has excellent potential as optical shutter for 3D imaging application.

Large aperture asymmetric Fabry Perot modulator based on asymmetric tandem quantum well for low voltage operation.

Large aperture image modulators used as demodulator in receiver path are an important component for the use in three dimensional (3D) image sensing. For practical applications, low voltage operation and high modulation performance are the key requirements for modulators. Here, we propose an asymmetric Fabry-Perot modulator (AFPM) with asymmetric tandem quantum wells (ATQWs) for 3D image sensing. By using ATQWs for the AFPM design, the device operated at -4.25V, and the operating voltage was significantly lower by about 23% compared to -5.5V of a conventional AFPM with 8nm thick multiple QW with a single QW thickness (SQWs), while achieving high reflectivity modulation in excess of 50%. The performance of the fabricated devices is in good agreement with theoretical calculations. The pixelated device shows a high modulation speed of 21.8 MHz over a large aperture and good uniformity. These results show that AFPM with ATQWs is a good candidate as an optical image modulator for 3D image sensing applications.