Comparison of Wrist and Forearm EMG for Multi-day Biometric Authentication.

Recently, electromyography (EMG) has been established as a promising new biometric trait that provides a unique dual mode security: biometrics and knowledge. For authentication that is used daily and long-term by general consumers, the wrist is a suitable location, which could be easily integrated into the existing form of smartwatches and fitness trackers. However, current EMG-based biometrics still follow the historical path of powered prosthetics research, where EMG signals were usually recorded from forearm positions. Moreover, the robustness of EMG processing algorithms across multiple days is still an open problem that needs to be addressed before for long-term reliable use. This study intends to investigate the difference in authentication performance between wrist and forearm EMG signals, in a within-day and two cross-day analyses. Our open dataset (GRABMyo dataset) was used to examine this difference, which contains forearm and wrist EMG data collected from 43 participants over three different days with long separation (Days 1, 8, and 29). The results showed wrist EMG signals led to at least comparable with forearm EMG signals in within-day Equal-error rate (EER). In cross-day analysis, the EER of the wrist EMG signals was higher than that of forearm signals. In general, the low median EER (<0.1) of wrist EMG in cumulative cross-day analysis demonstrates the promise of using wrist EMG signals for authentication in long-term applications.

Cross-day analysis of Multicode Surface Electromyography based Biometrics for Personal Identification.

Recently, surface electromyography (sEMG) has emerged as a novel biometric trait for personal identification, potentially providing a superior spoof-resistant solution over existing traits. The sEMG possesses a unique dual-mode security: they differ between individuals (biometric-mode), and different gestures have different sEMG characteristics (knowledge-mode). To leverage the knowledge-mode facet of the dual-mode security, the previous studies have utilized a multicode framework involving the fusion of codes (gestures), however, the analysis involved data recorded on a single day and from a small subject-pool. In this study, wrist EMG data collected from 43 participants over three different days while performing static hand/wrist gestures was utilized in two cross-day analyses, where the training and testing data were from different days. Three levels of fusion, score, rank, and decision were investigated to determine the optimal fusion scheme. The results showed that the score-level fusion scheme resulted in a median rank-1 accuracy of 77.9% and rank-5 accuracy of 99.6%, all significantly higher (p<0.001) than the respective single-code gesture. Our results showed that the multicode sEMG biometric framework provides superior identification performance in a more realistic cross-day scenario.

Waterborne exposure during non-consumptive domestic use of surface water: a population study across WASH service levels in rural India.

Exposure to pathogens from domestic use of surface water is understudied. In many low- and middle-income countries, surface water is used for hygiene, sanitation, amenity, and recreational purposes. In this study, self-reported use of and structured observations at community ponds were collected to measure waterborne exposure across water and sanitation service levels in a rural population of Khorda District, India. Overall, 86% of households (n = 200) reported using ponds on a regular basis. Among observed people (n = 765), 82% put water into their mouth at least once, with a median frequency of five occurrences per visit. Reported and observation data were combined to estimate the proportion (p) of the population that put water in their mouth at least once per day, and their mean daily rate of oral exposure (OE). These were highest for individuals with neither safely managed water nor basic sanitation access (p = 93%, OE = 14 day-1), but still high among those with both (p = 67%, OE = 6 day-1). The results suggest widespread exposure to waterborne pathogens in settings where non-potable surface water bodies continue to be used for domestic purposes, even among households with access to safely managed drinking water.

Effectiveness of Fortified Mid-Day Meal in Reducing Anemia Among School Children in Dhenkanal, Odisha: A Quasi-Experimental Study.

BACKGROUND: Iron-deficiency anemia among school-aged children is widespread in India. The efficacy of micronutrient and iron fortified school-served meals in reducing iron deficiency anemia has been demonstrated in randomized controlled trials in other parts of the globe. The current study evaluates its effectiveness in real-world Indian settings. METHODS: Mid-day-Meal (MDM) programme provides free lunch to students of grades 1 to 8 in all public-funded Indian schools. An implementation research project fortified MDM of all public schools of 4 out of 8 sub-districts ("blocks") of Dhenkanal district of Odisha state with fortified rice kernel (FRK). All the schools of the other 4 blocks fortified with micronutrient powders (MNP)-both FRK and MNP containing equal amounts of supplementary iron and other micronutrients. Schools of 4 matched blocks of neighboring nonimplementing Angul district served as control. Cross-sectional representative samples of students were drawn from the 3 arms, before and after intervention (n = 1764 and n = 1640 respectively). Pre-post changes in anemia prevalence and hemoglobin levels were estimated in the sampled children using difference-in-difference analysis after controlling for inter-arm differences in socioeconomic status, and iron and deworming tablet consumptions. RESULTS: Factoring in pre-post changes in control and adjusting for potential confounders, the proportion of children without anemia and mean hemoglobin improved by 1.93 (1.38, 2.24, P < .001) times and 0.24 (-0.03, 0.51, P = .083) g/dL in MNP; and 1.63 (1.18, 2.24, P = .002) times and 0.18 (-0.09, 0.45, P = .198) g/dL in FRK arms. CONCLUSIONS: Fortified MDM could effectively improve anemia status among Indian school-aged children under real-world conditions.

Multi-day dataset of forearm and wrist electromyogram for hand gesture recognition and biometrics.

Surface electromyography (sEMG) signals have been used for advanced prosthetics control, hand-gesture recognition (HGR), and more recently as a novel biometric trait. For these sEMG-based applications, the translation from laboratory research setting to real-life scenarios suffers from two major limitations: (1) a small subject pool, and (2) single-session data recordings, both of which prevents acceptable generalization ability. In this longitudinal database, forearm and wrist sEMG data were collected from 43 participants over three different days with long separation (Days 1, 8, and 29) while they performed static hand/wrist gestures. The objective of this dataset is to provide a comprehensive dataset for the development of robust machine learning algorithms of sEMG, for both HGR and biometric applications. We demonstrated the high quality of the current dataset by comparing with the Ninapro dataset. And we presented its usability for both HGR and biometric applications. Among other applications, the dataset can also be used for developing electrode-shift invariant generalized models, which can further bolster the development of wristband and forearm-bracelet sensors.

Classification of Autism and Control Gait in Children Using Multisegment Foot Kinematic Features.

Previous research has demonstrated that children with autism walk with atypical ankle kinematics and kinetics. Although these studies have utilized single-segment foot (SSF) data, multisegment foot (MSF) kinematics can provide further information on foot mechanics. Machine learning (ML) tools allow the combination of MSF kinematic features for classifying autism gait patterns. In this study, multiple ML models are investigated, and the most contributing features are determined. This study involved 19 children with autism and 21 age-matched controls performing walking trials. A 34-marker system and a 12-camera motion capture system were used to compute SSF and MSF angles during walking. Features extracted from these foot angles and their combinations were used to develop support vector machine (SVM) models. Additional techniques-S Hapley Additive exPlanations (SHAP) and the Shapley Additive Global importancE (SAGE) are used for local and global importance of the black-box ML models. The results suggest that models based on combinations of MSF kinematic features classify autism patterns with an accuracy of 96.3%, which is higher than using SSF kinematic features (83.8%). The relative angle between the metatarsal and midfoot segments had the highest contribution to the classification of autism gait patterns. The study demonstrated that kinematic features from MSF angles, supported by ML models, can provide an accurate and interpretable classification of autism and control patterns in children.

Score, Rank, and Decision-Level Fusion Strategies of Multicode Electromyogram-Based Verification and Identification Biometrics.

Recent advances in biometric research have established surface electromyogram (sEMG) as a potential spoof-free solution to address some key limitations in current biometric traits. The nature of sEMG signals provide a unique dual-mode security: sEMGs have individual-specific characteristics (biometrics), and users can customize and change gestures just like passcodes. Such security also facilitates the use of code sequences (multicode) to further enhance the security. In this study, three levels of fusion, score, rank, and decision were investigated for two biometric applications, verification and identification. This study involved 24 subjects performing 16 hand/finger gestures, and code sequences with varying codelengths were generated. The performance of the verification and identification system was analyzed for varying codelength (M: 1-6) and rank (K: 1-4) to determine the best fusion scheme and desirable parameter values for a multicode sEMG biometric system. The results showed that the decision-level fusion scheme using a weighted majority voting resulted in an average equal error rate of 0.6% for the verification system when M = 4. For the identification system, the score-level fusion scheme with score normalization based on fitting a Weibull distribution resulted in a minimum false rejection rate of 0.01% and false acceptance rate of 4.7% using a combination of K = 2 and M = 4. The results also suggested that the parameters M and K could be adjusted based on the number of users in the database to facilitate optimal performance. In summary, a multicode sEMG biometric system was developed to provide improved dual-mode security based on the personalized codes and biometric traits of individuals, with the combination of enhanced security and flexibility.

High-Density Electromyography Provides Improved Understanding of Muscle Function for Those With Amputation.

Transtibial amputation can significantly impact an individual's quality of life including the completion of activities of daily living. Those with lower limb amputations can harness the electrical activity from their amputated limb muscles for myoelectric control of a powered prosthesis. While these devices use residual muscles from transtibial-amputated limb as an input to the controller, there is little research characterizing the changes in surface electromyography (sEMG) signal generated by the upper leg muscles. Traditional surface EMG is limited in the number of electrode sites while high-density surface EMG (HDsEMG) uses multiple electrode sites to gather more information from the muscle. This technique is promising for not only the development of myoelectric-controlled prostheses but also advancing our knowledge of muscle behavior with clinical populations, including post-amputation. The HDsEMG signal can be used to develop spatial activation maps and features of these maps can be used to gain valuable insight into muscle behavior. Spatial features of HDsEMG can provide information regarding muscle activation, muscle fiber heterogeneity, and changes in muscle distribution and can be used to estimate properties of both the amputated limb and intact limb. While there are a few studies that have examined HDsEMG in amputated lower limbs they have been limited to movements such as gait. The purpose of this study was to examine the quadriceps muscle during a slow, moderate and fast isokinetic knee extensions from a control group as well as a clinical patient with a transtibial amputation. HDsEMG was collected from the quadriceps of the dominant leg of 14 young, healthy males (mean age = 25.5 ± 7 years old). Signals were collected from both the intact and amputated limb muscle of a 23 year old clinical participant to examine differences between the affected and unaffected leg. It was found that there were differences between the intact and amputated limb limb of the clinical participant with respect to muscle activation and muscle heterogeneity. While this study was limited to one clinical participant, it is important to note the differences in muscle behavior between the intact and amputated limb limb. Understanding these differences will help to improve training protocols for those with amputation.

Effect of age and sex on strength and spatial electromyography during knee extension.

BACKGROUND: Multichannel surface electromyography (EMG) is a method to examine properties of motor unit (MU) activity using multiple electrodes arranged on a two-dimensional grid. This technique can be used to examine alterations in EMG activity distribution due to contraction intensity as well as due to physiological differences such as age or sex. Therefore, the purpose of this study was to compare strength and high-density surface EMG (HDsEMG) features during isometric and isokinetic knee extensions between older and younger men and women. METHODS: Twenty younger (ages 19-25 years) and twenty older (ages 64-78) men and women performed submaximal and maximal isometric (at a joint angle of 90°) and isokinetic knee extensions, while HDsEMG was recorded from the vastus lateralis. Spatial distribution was estimated using the root mean square (RMS), and 2-dimensional (2D) maps were developed to examine spatial features. Coefficient of variation (CV) and modified entropy were used to examine alterations in muscle heterogeneity and pattern. Peak torque and HDsEMG parameters were compared across age and gender. RESULTS: Younger males and females produced significantly higher mean torque than the older group (p < 0.001) for all contractions. Both age- and sex-related significant differences (p < 0.05) were found for EMG spatial features suggesting neuromuscular differences. Modified entropy was significantly higher and CV was lower for young females compared to young males (p < 0.05) across both isometric and isokinetic contractions. CONCLUSIONS: We found that isometric and isokinetic knee extension strength, spatial distribution, and intensity differ as a function of age and sex during knee extensions. While there were no differences detected in entropy between age groups, there were sex-related differences in the younger age category. The lack of age-related differences in entropy was surprising given the known effects of aging on muscle fiber composition. However, it is often reported that muscle coactivation increases with age and this work was limited to the study of one muscle of the knee extensors (vastus lateralis) which should be addressed in future work. The findings suggest while both age and sex affect muscle activation, sex had a greater effect on heterogeneity. The results obtained will help to develop improved rehabilitation programs for aging men and women.

Trends in Malaria in Odisha, India-An Analysis of the 2003-2013 Time-Series Data from the National Vector Borne Disease Control Program.

BACKGROUND: Although Odisha is the largest contributor to the malaria burden in India, no systematic study has examined its malaria trends. Hence, the spatio-temporal trends in malaria in Odisha were assessed against the backdrop of the various anti-malaria strategies implemented in the state. METHODS: Using the district-wise malaria incidence and blood examination data (2003-2013) from the National Vector Borne Disease Control Program, blood examination-adjusted time-trends in malaria incidence were estimated and predicted for 2003-2013 and 2014-2016, respectively. An interrupted time series analysis using segmented regression was conducted to compare the disease trends between the pre (2003-2007) and post-intensification (2009-2013) periods. Key-informant interviews of state stakeholders were used to collect the information on the various anti-malaria strategies adopted in the state. RESULTS: The state annual malaria incidence declined from 10.82/1000 to 5.28/1000 during 2003-2013 (adjusted annual decline: -0.54/1000, 95% CI: -0.78 to -0.30). However, the annual blood examination rate remained almost unchanged from 11.25% to 11.77%. The keyinformants revealed that intensification of anti-malaria activities in 2008 led to a more rapid decline in malaria incidence during 2009-2013 as compared to that in 2003-2007 [adjusted decline: -0.83 (-1.30 to -0.37) and -0.27 (-0.41 to -0.13), respectively]. There was a significant difference in the two temporal slopes, i.e., -0.054 (-0.10 to -0.002, p = 0.04) per 1000 population per month, between these two periods, indicating almost a 200% greater decline in the post-intensification period. Although, the seven southern high-burden districts registered the highest decline, they continued to remain in that zone, thereby, making the achievement of malaria elimination (incidence <1/1000) unlikely by 2017. CONCLUSION: The anti-malaria strategies in Odisha, especially their intensification since 2008, have helped improve its malaria situation in recent years. These successful measures need to be sustained and perhaps intensified further for eliminating malaria from Odisha.