Development of a novel device for monitoring incentive spirometry performance

Lung atelectasis caused by shallow breathing patterns is common after cardiac, thoracic and upper abdominal surgeries. A common method used to address this problem is to encourage patients to perform breathing exercises using incentive spirometers in the postoperative period. However, to be effective, this procedure must be repeated regularly so that adequate lung volumes can be maintained to prevent atelectasis. Current models of single-use, low-cost incentive spirometers do not have features that can track and store data on breathing exercises. This makes it difficult to monitor patients’ breathing exercises effectively. We present here a device designed to be interfaced with the Spiro-ball incentive spirometer and programmed to monitor the incentive spirometry performance. Laboratory based validation performed indicate that there were no significant differences between the value obtained from the device and manual reading; p-value > 0.05 and root-mean-square error (RMSE) is 3.882. The device was able to retrieve and display pertinent data on incentive spirometry performance. It was also able to correctly track and register random sets of inspiration data through different dates and timelines. Being a separate entity which is reusable, it does not add to the cost of the single-use incentive spirometer

Fabrication of low-cost, cementless femoral stem 316L stainless steel using investment casting technique

Total hip arthroplasty is a flourishing orthopedic surgery, generating billions of dollars of revenue. The cost associated with the fabrication of implants has been increasing year by year, and this phenomenon has burdened the patient with extra charges. Consequently, this study will focus on designing an accurate implant via implementing the reverse engineering of three-dimentional morphological study based on a particular population. By using finite element analysis, this study will assist to predict the outcome and could become a useful tool for preclinical testing of newly designed implants. A prototype is then fabricated using 316L stainless steel by applying investment casting techniques that reduce manufacturing cost without jeopardizing implant quality. The finite element analysis showed that the maximum von Mises stress was 66.88MPa approximately with a safety factor of 2.39 against endosteal fracture, and micromotion was 4.3um, which promotes osseointegration. This method offers a fabrication process of comentless femoral stems with lower cost, subsequently helping patients, particularly those from nondeveloped countries

Brain-computer interface algorithm based on wavelet-phase stability analysis in motor imagery experiment

Severe movement or motor disability diseases such as amyotrophic lateral sclerosis (ALS), cerebral palsy (CB), and muscular dystrophy (MD) are types of diseases which lead to the total of function loss of body parts, usually limbs. Patient with an extreme motor impairment might suffers a lockedin state, resulting in the difficulty to perform any physical movements. These diseases are commonly being treated by a specific rehabilitation procedure with prescribed medication. However, the recovery process is time-consuming through such treatments. To overcome these issues, Brain- Computer Interface system is introduced in which one of its modalities is to translate thought via electroencephalography (EEG) signals by the user and generating desired output directly to an external artificial control device or human augmentation. Here, phase synchronization is implemented to complement the BCI system by analyzing the phase stability between two input signals. The motor imagery-based experiment involved ten healthy subjects aged from 24 to 30 years old with balanced numbers between male and female. Two aforementioned input signals are the respective reference data and the real time data were measured by using phase stability technique by indicating values range from 0 (least stable) to 1 (most stable). Prior to that, feature extraction was utilized by applying continuous wavelet transform (CWT) to quantify significant features on the basis of motor imagery experiment which are right and left imaginations. The technique was able to segregate different classes of motor imagery task based on classification accuracy. This study affirmed the approach’s ability to achieve high accuracy output measurements

Formulation of a novel HRV classification model as a surrogate fraudulence detection schema

Lie detection has been studied since a few decades ago, usually for the purpose of producing a scheme to assist in the investigation of identifying the culprit from a list of suspects. Heart Rate Variability (HRV) may be used as a method in lie detection due to its versatility and suitability. However, since its analysis is not instantaneous, a new experiment is described in this paper to overcome the problem. Additionally, a preliminary HRV classification model is designed to further enhance the classification model which is able to distinguish the lie from the truth for up to 80%

Heart sound feature representation using extended modified bdistribution

Heart sound analysis has gathered increasing attention over the past few years as the maturity of processing algorithms start to produce reliable and promising results. This work highlights the advantages of recently developed time frequency method which is Modified B-Distribution (MBD) and Extended Modified B-Distribution (EMBD). The approach was tested against real subjects with normal and abnormal type of heart sound and murmurs. The result shows that the EMBD is able to reveal more valuable murmurs signal as compared to MBD which provides the vital information in detecting the presence of heart disease

Classification of heart sound based on multipoint auscultation system

Heart disorder can be diagnosed by listening to the heart sound that is recorded using stethoscope on the human chest. However, human interpretation and diagnosis based on auscultation is somewhat subjective and vary depending on the skill and hearing ability of the physician. Studies have been focusing on the development and evaluation of methods in detecting the various components of the heart sound at a specific auscultation point. The principle interest of this paper is, however focused towards finding the optimal auscultation point which involves placing the stethoscope at different position namely at the aortic valve and pulmonary valve which provide better quality of the second heart sound component (S2) and mitral valve and tricuspid valve where the first heart sound component (Sl) can be heard more clearly. Comparative experiments using to Mel-Frequency Cepstrum Coefficient (MFCC) property, variation of the number of Hidden markov Model (HMM) states and variation of the number of gaussian mixtures were conducted to measure the offects of these factors to the classification performance at the four locations of auscultation point. Further works was also carried out with time-frequency distribution which is known to provide information about how the spectral content of the signal evolves with time. The Extended Modified B-distribution was chosen from a number of time-frequency methods due to its ability to represent the signal in the most efficient way in term of noise and cross term elimination

Design process of cementless femoral stem using a nonlinear three dimensional finite element analysis

Background: Minimal available information concerning hip morphology is the motivation for several researchers to study the difference between Asian and Western populations. Current use of a universal hip stem of variable size is not the best option for all femur types. This present study proposed a new design process of the cementless femoral stem using a three dimensional model which provided more information and accurate analysis compared to conventional methods. Methods. This complete design cycle began with morphological analysis, followed by femoral stem design, fit and fill analysis, and nonlinear finite element analysis (FEA). Various femur parameters for periosteal and endosteal canal diameters are measured from the osteotomy level to 150 mm below to determine the isthmus position. Results: The results showed better total fit (53.7%) and fill (76.7%) canal, with more load distributed proximally to prevent stress shielding at calcar region. The stem demonstrated lower displacement and micromotion (less than 40 μm) promoting osseointegration between the stem-bone and providing primary fixation stability. Conclusion: This new design process could be used as a preclinical assessment tool and will shorten the design cycle by identifying the major steps which must be taken while designing the femoral ste

Primary stability recognition of the newly designed cementless femoral stem using digital signal processing

Stress shielding and micromotion are two major issues which determine the success of newly designed cementless femoral stems.The correlation of experimental validation with finite element analysis (FEA) is commonly used to valuate the stress distribution and fixation stability of the stem within the femoral canal. This paper focused on the applications of feature extraction and pattern recognition using support vector machine (SVM) to determine the primary stability of the implant. We measured strain with triaxial rosette at the metaphyseal region and micromotion with linear variable direct ransducer proximally and distally using composite femora. The root mean squares technique is used to feed the classifier which provides maximum likelihood estimation of amplitude, and radial basis function is used as the kernel parameter which mapped the datasets into separable hyperplanes.The results showed 100% pattern recognition accuracy using SVM for both strain and micromotion.This indicates that DSP could be applied in determining the femoral stem primary stability with high pattern recognition accuracy in biomechanical testing