Finger Sensor Research Articles

Non-Contact Heart Rate and Blood Pressure Estimations from Video Analysis and Machine Learning Modelling Applied to Food Sensory Responses: A Case Study for Chocolate.

Traditional methods to assess heart rate (HR) and blood pressure (BP) are intrusive and can affect results in sensory analysis of food as participants are aware of the sensors. This paper aims to validate a non-contact method to measure HR using the photoplethysmography (PPG) technique and to develop models to predict the real HR and BP based on raw video analysis (RVA) with an example application in chocolate consumption using machine learning (ML). The RVA used a computer vision algorithm based on luminosity changes on the different RGB color channels using three face-regions (forehead and both cheeks). To validate the proposed method and ML models, a home oscillometric monitor and a finger sensor were used. Results showed high correlations with the G color channel (R2 = 0.83). Two ML models were developed using three face-regions: (i) Model 1 to predict HR and BP using the RVA outputs with R = 0.85 and (ii) Model 2 based on time-series prediction with HR, magnitude and luminosity from RVA inputs to HR values every second with R = 0.97. An application for the sensory analysis of chocolate showed significant correlations between changes in HR and BP with chocolate hardness and purchase intention.

Between Individual Variability in Sleep and Awake Pulse Oximetry During Ascent Of Mt. Kilimanjaro

Between individual variability in awake arterial pulse oximetry (aSpO2) is well known and has been proposed for field assessment of altitude acclimatization. Sleep SpO2 (sSpO2) is known to be lower than aSpO2 at high altitude, but the between individual variability in sSpO2 is not as well known. PURPOSE: Compare between individual variability and relationship between sSpO2 and aSpO2 during a 6 day ascent of Mt. Kilimanjaro. METHODS: In 18 (12 men/6 women), age range 18-62 yr, low-altitude residents over 5 of 6 nights sSpO2 was assessed using a finger sensor recording pulse oximeter and compared to a morning aSpO2 measured for 1 minute while the subject was quietly seated. Each individual’s mean SpO2 was calculated for their sleep and awake measurements. Correlations (Pearson product-moment) between sleep and awake SpO2 were evaluated. RESULTS: As expected, both sSpO2 and aSpO2 decreased with increasing altitude. The Coefficient of Variation (CV), of both sSpO2 and aSpO2 increased with increasing altitude. Individual sSpO2 and the next morning aSpO2 were strongly correlated at all altitudes.Table: No title available.CONCLUSION: In low altitude residents climbing to 4830 m over 6 days, sleep and awake SpO2 have similar between subject variability (dispersion) that more than doubles with increasing altitude indicating a broadening of individual ventilation and pulmonary gas exchange responses to the hypoxic environment. Also, individual sSpO2 and aSpO2 are highly correlated to each other. Funding: USAMRMC. The views expressed in this abstract are those of the authors and do not reflect the official policy of the Department of Army, Department of Defense, or the U.S. Government.

Quantitative Analysis of Bradykinesia and Rigidity in Parkinson's Disease.

In the last decades, several studies showed that wearable sensors, used for assessing Parkinson's disease (PD) motor symptoms and recording their fluctuations, could provide a quantitative and reliable tool for patient's motor performance monitoring. The aim of this study is to make a step forward the capability of quantitatively describing PD motor symptoms. The specific aims are: identify the most sensible place where to locate sensors to monitor PD bradykinesia and rigidity, and identify objective indexes able to discriminate PD OFF/ON motor status, and PD patients from healthy subjects (HSs). Fourteen PD patients (H&Y stage 1-2.5), and 13 age-matched HSs, were enrolled. Five magneto-inertial wearable sensors, placed on index finger, thumb, metacarpus, wrist, and arm, were used as motion tracking systems. Sensors were placed on the most affected arm of PD patients, and on dominant hand of HS. Three UPDRS part III tasks were evaluated: rigidity (task 22), finger tapping (task 23), and prono-supination movements of the hands (task 25). A movement disorders expert rated the three tasks according to the UPDRS part III scoring system. In order to describe each task, different kinematic indexes from sensors were extracted and analyzed. Four kinematic indexes were extracted: fatigability; total time; total power; smoothness. The last three well-described PD OFF/ON motor status, during finger-tapping task, with an index finger sensor. During prono-supination task, wrist sensor was able to differentiate PD OFF/ON motor condition. Smoothness index, used as a rigidity descriptor, provided a good discrimination of the PD OFF/ON motor status. Total power index, showed the best accuracy for PD vs healthy discrimination, with any sensor location among index finger, thumb, metacarpus, and wrist. The present study shows that, in order to better describe the kinematic features of Parkinsonian movements, wearable sensors should be placed on a distal location on upper limb, on index finger or wrist. The proposed indexes demonstrated a good correlation with clinical scores, thus providing a quantitative tool for research purposes in future studies in this field.

RF interferometric wearable wrist pulse detection system

This study presents a novel wrist pulse detection system based on the variation of transmission coefficient ( S 21 ) of coupled resonators. Radiated signal from one resonator is modulated by the wrist pulse and transmitted to the other resonator. To improve sensitivity of the system, a radio-frequency (RF) interferometer concept is employed and its validity is mathematically analysed. Full-wave electromagnetic simulation is conducted with the wrist phantom model to predict the transmission coefficient between resonators. The peak level of the S 21 is around −10 dB and the resonance frequency shifts to higher frequency as the distance between the resonator and wrist increases. A prototype of the system is fabricated and tested to show sensitivity enhancement around the 2.4 GHz industry-science-medical (ISM) band. Experimental results reveal that the wrist pulse signal measured by the RF interferometer system is in exact coincidence with the reference finger sensor. Also, the sensitivity is enhanced about 23 dB with the RF interferometer system based on the measurement results.

Finger and foot tapping sensor system for objective motor assessment

Background/Aim. Finger tapping test is commonly used in neurological examinations as a test of motor performance. The new system comprising inertial and force sensors and custom proprietary software was developed for quantitative estimation and assessment of finger and foot tapping tests. The aim of this system was to provide diagnosis support and objective assessment of motor function. Methods. Miniature inertial sensors were placed on fingertips and used for measuring finger movements. A force sensor was placed on the fingertip of one finger, in order to measure the force during tapping. For foot tapping assessment, an inertial sensor was mounted on the subject?s foot, which was placed above a force platform. By using this system, various parameters such as a number of taps, tapping duration, rhythm, open and close speed, the applied force and tapping angle, can be extracted for detailed analysis of a patient?s motor performance. The system was tested on 13 patients with Parkinson?s disease and 14 healthy controls. Results. The system allowed easy measurement of listed parameters, and additional graphical representation showed quantitative differences in these parameters between neurological patient and healthy subjects. Conclusion. The novel system for finger and foot tapping test is compact, simple to use and efficiently collects patient data. Parameters measured in patients can be compared to those measured in healthy subjects, or among groups of patients, or used to monitor progress of the disease, or therapy effects. Created data and scores could be used together with the scores from clinical tests, providing the possibility for better insight into the diagnosis.

超音波生体指センサによる指荷重と表面性状評価の試み

超音波生体指センサによる指荷重と表面性状評価の試み

Comparison of Spontaneous versus Paced Breathing on Heart Rate Variability at High Altitude

© 2018, Journal of Clinical and Diagnostic Research. All rights reserved. Introduction: There is conflicting data at sea-level to suggest that Paced Breathing (PB) versus Spontaneous Breathing (SB) during short-term Heart Rate Variability (HRV) measurement improves data reliability. Aim: This study sought to examine the effects of SB versus PB on HRV, at High Altitude (HA). Materials and Methods: This was a prospective observational study on thirty healthy adult men who were investigated over nine days at altitudes of 800-4107 m. Cardiac inter-beat interval data were measured over 55 seconds, twice daily, using an ithlete finger sensor linked to a mobile phone to generate a HRV score. Agreements in the paired (SB vs PB) HRV scores were examined using paired t-tests, correlation coefficients and F-Testing. A factorial repeated measures ANOVA was used to examine the main effect of altitude and breathing method on the paired differences in HRV scores. Results: HA led to a significant reduction in SpO2 and increase in Acute Mountain Sickness (AMS) Scores. HRV scores (511 paired scores) were consistently higher with PB versus SB (mean difference +6.0; 96.1% within 95% agreement limit), though the variance was lower (F=1.2; p=0.04) and the scores strongly correlated (r=0.78; p<0.0001). HRV scores were lower with AMS (versus without AMS), but this difference was only significant with SB (68.1±12.1 vs. 74.3±11.4 vs; p=0.03) but not PB (76.3±11.8 vs. 80.3±10.4 vs; p=0.13). There was a significant main-effect for altitude (F=5.3; p<0.0001) and breathing (F=262.1; p<0.0001) on HRV scores but no altitude-x-breathing interaction (F=1.2; p=0.30). Conclusion: Ithlete HRV scores obtained with PB and SB strongly correlate at moderate HA but are consistently higher and the variance lower with PB. Whilst the actual per se does not affect this difference, the presence of AMS may be an important confounder.

Motion artefact minimization from photoplethysmography based non-invasive hemoglobin sensor based on an envelope filtering algorithm

An envelope-filtered method of enhancement of non-invasive Hemoglobin (Hb) monitoring is described. Results using a four-wavelength two-wavelength Photoplethysmography (PPG) probe gathered from five randomly selected healthy subjects demonstrate that the measurement of Hb coefficient, based on the novel envelope method filtered PPG, has a superior performance on minimization of the motion artefact than that from band-pass filtered PPG data in both stationary and non-stationary scenarios. Hemodynamic pressure variation near the sensor probe is also induced from a vertical height difference (VHD) between the finger sensor probe and the heart level. Results of this study show that the Hb coefficients determined using the proposed filtering method based on the envelope algorithm are also capable of minimization of VHD variations similar to the traditional band-pass filter method.

Non-magnetic compliant finger sensor for continuous fine motor movement detection.

A non-magnetic MEG compatible device has been developed that provides continuous force and velocity information. Combined with MEG, this device may find utility in characterizing brain regions associated with force and velocity relative to individual digits or movement pattern. 15 healthy right-handed participants were given visual cues to perform random finger movements on the prototype finger sensor for 21s and then rest for 21s (7 times). Respective finger flexion data were obtained, during 151-channel MEG brain scanning, by feeding the signal from finger sensor into four input Analog to Digital Converter (ADC) channels in the MEG hardware. The source activity was reconstructed in beta band using a Linearly Constrained Minimum Variance (LCMV) beamformer in the beta band. The ADC channels were used as regressors for a continuous time General Linear Model (GLM) and a Region of Interest (ROI) was identified to examine activity. MEG analysis showed bilateral activation in the primary motor cortex region. Because individual digits could be isolated in the ADC data, somatotopy of the fingers were observed consistent with the homunculus except pinky finger. The total span was calculated to be 5.5662mm. The study confirms that the finger sensor is magnetically compatible with MEG measurements and may potentially provide a means to study complex sensorimotor functions. Improved isolation of individual digit information along with the use of machine learning algorithms can help retrieve more accurate results.

Comparison the Precision of Ear and Finger Pulse Oximetry with Finger Sensor in Mechanically Ventilated ICU Patients

Comparison the Precision of Ear and Finger Pulse Oximetry with Finger Sensor in Mechanically Ventilated ICU Patients

In vivo investigation of ear canal pulse oximetry during hypothermia

Pulse oximeters rely on the technique of photoplethysmography (PPG) to estimate arterial oxygen saturation (SpO_2). In conditions of poor peripheral perfusion such as hypotension, hypothermia, and vasoconstriction, the PPG signals detected are often weak and noisy, or in some cases unobtainable. Hence, pulse oximeters produce erroneous SpO_2 readings in these circumstances. The problem arises as most commercial pulse oximeter probes are designed to be attached to peripheral sites such as the finger or toe, which are easily affected by vasoconstriction. In order to overcome this problem, the ear canal was investigated as an alternative site for measuring reliable SpO_2 on the hypothesis that blood flow to this central site is preferentially preserved. A novel miniature ear canal PPG sensor was developed along with a state of the art PPG processing unit to investigate PPG measurements from the bottom surface of the ear canal. An in vivo study was carried out in 15 healthy volunteers to validate the developed technology. In this comparative study, red and infrared PPGs were acquired from the ear canal and the finger of the volunteers, whilst they were undergoing artificially induced hypothermia by means of cold exposure (10 ^circC). Normalised Pulse Amplitude (NPA) and SpO_2 was calculated from the PPG signals acquired from the ear canal and the finger. Good quality baseline PPG signals with high signal-to-noise ratio were obtained from both the PPG sensors. During cold exposure, significant differences were observed in the NPA of the finger PPGs. The mean NPA of the red and infrared PPGs from the finger have dropped by >80%. Contrary to the finger, the mean NPA of red and infrared ear canal PPGs had dropped only by 0.2 and 13% respectively. The SpO_2s estimated from the finger sensor have dropped below 90% in five volunteers (failure) by the end of the cold exposure. The ear canal sensor, on the other hand, had only failed in one volunteer. These results strongly suggest that the ear canal may be used as a suitable alternative site for monitoring PPGs and arterial blood oxygen saturation at times were peripheral perfusion is compromised.

Measurement of finger joint angle using a flexible polymer sensor

This paper aims to develop a measurement system for the finger joint angle by using a flexible polymer sensor. In rehabilitation, it is important to evaluate human motions quantitatively for effective treatment. In this study, we focus on hand's grasping motion, which is important motion for eating and drinking. About the flexible polymer sensor, in the previous studies, it has been elucidated that the outputs from the flexible polymer sensor are proportional to the average curvature of measuring surface. Therefore, using the sensor, finger bending motion can be measured by attaching the sensor on finger surface. Firstly, the relationship between the average curvature of finger surface and finger joint angle is theoretically investigated. Then, in order to obtain the relationship between sensor outputs and finger joint angles, sensor outputs and finger joint angles during grasping acrylic cylinders are measured. From the results, it was found that the developed system is useful to measure the finger joint angles.

Heart beat characterization from ballistocardiogram signals using extended functions of multiple instances.

A multiple instance learning (MIL) method, extended Function of Multiple Instances (eFUMI), is applied to ballistocardiogram (BCG) signals produced by a hydraulic bed sensor. The goal of this approach is to learn a personalized heartbeat "concept" for an individual. This heartbeat concept is a prototype (or "signature") that characterizes the heartbeat pattern for an individual in ballistocardiogram data. The eFUMI method models the problem of learning a heartbeat concept from a BCG signal as a MIL problem. This approach elegantly addresses the uncertainty inherent in a BCG signal (e. g., misalignment between training data and ground truth, mis-collection of heartbeat by some transducers, etc.). Given a BCG training signal coupled with a ground truth signal (e.g., a pulse finger sensor), training "bags" labeled with only binary labels denoting if a training bag contains a heartbeat signal or not can be generated. Then, using these bags, eFUMI learns a personalized concept of heartbeat for a subject as well as several non-heartbeat background concepts. After learning the heartbeat concept, heartbeat detection and heart rate estimation can be applied to test data. Experimental results show that the estimated heartbeat concept found by eFUMI is more representative and a more discriminative prototype of the heartbeat signals than those found by comparison MIL methods in the literature.

Compliant finger sensor for sensorimotor studies in MEG and MR environment

Magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) are widely used for functional brain imaging. The correlations between the sensorimotor functions of the hand and brain activities have been investigated in MEG/fMRI studies. Currently, limited information can be drawn from these studies due to the limitations of existing motion sensors that are used to detect hand movements. One major challenge in designing these motion sensors is to limit the signal interference between the motion sensors and the MEG/fMRI. In this work, a novel finger motion sensor, which contains low-ferromagnetic and non-conductive materials, is introduced. The finger sensor consists of four air-filled chambers. When compressed by finger(s), the pressure change in the chambers can be detected by the electronics of the finger sensor. Our study has validated that the interference between the finger sensor and an MEG is negligible. Also, by applying a support vector machine algorithm to the data obtained from the finger sensor, at least 11 finger patterns can be discriminated. Comparing to the use of traditional electromyography (EMG) in detecting finger motion, our proposed finger motion sensor is not only MEG/fMRI compatible, it is also easy to use. As the signals acquired from the sensor have a higher SNR than that of the EMG, no complex algorithms are required to detect different finger movement patterns. Future studies can utilize this motion sensor to investigate brain activations during different finger motions and correlate the activations with the sensory and motor functions respectively.

Optical Myography: Detecting Finger Movements by Looking at the Forearm.

One of the crucial problems found in the scientific community of assistive/rehabilitation robotics nowadays is that of automatically detecting what a disabled subject (for instance, a hand amputee) wants to do, exactly when she wants to do it, and strictly for the time she wants to do it. This problem, commonly called “intent detection,” has traditionally been tackled using surface electromyography, a technique which suffers from a number of drawbacks, including the changes in the signal induced by sweat and muscle fatigue. With the advent of realistic, physically plausible augmented- and virtual-reality environments for rehabilitation, this approach does not suffice anymore. In this paper, we explore a novel method to solve the problem, which we call Optical Myography (OMG). The idea is to visually inspect the human forearm (or stump) to reconstruct what fingers are moving and to what extent. In a psychophysical experiment involving ten intact subjects, we used visual fiducial markers (AprilTags) and a standard web camera to visualize the deformations of the surface of the forearm, which then were mapped to the intended finger motions. As ground truth, a visual stimulus was used, avoiding the need for finger sensors (force/position sensors, datagloves, etc.). Two machine-learning approaches, a linear and a non-linear one, were comparatively tested in settings of increasing realism. The results indicate an average error in the range of 0.05–0.22 (root mean square error normalized over the signal range), in line with similar results obtained with more mature techniques such as electromyography. If further successfully tested in the large, this approach could lead to vision-based intent detection of amputees, with the main application of letting such disabled persons dexterously and reliably interact in an augmented-/virtual-reality setup.

Temperature prediction with humanoid finger sensor based on Fourier’s law

BioTac is a humanoid finger sensor that can perceive multiple physical properties such as temperature, contact force, surface features, micro-vibration, etc. However measuring temperature with BioTac has a large delay due to its conducting medium, which is unfavorable for intelligent perception. So a method of temperature prediction based on Fourier’s Law is proposed. Firstly, a multi-functional calibration device for BioTac is built. Secondly, the pressure signal of BioTac is calibrated for the next temperature calibration. Thirdly, the relational expression between the temperature signal from BioTac and the actual temperature is given using the Least Square method. Then the calculated temperature according to the relational expression is compensated by thermal flux, which is the predicted temperature. Finally, the proposed method is verified using the calibration device. The results show that the proposed method can greatly reduce the time of measuring temperature, and the prediction accuracy meets the demand of application.

A Review on the Design of Non-Contact Vital Signs (NCVS) Biosensors for Long-Term Continuous Monitoring

It has been the dream of many scientists and engineers to realize a non-contact remote biosensing system that can perform continuous, accurate, and long-term monitoring of human vital signs as what we saw in some SciFi movies. Having a system that can measure and record key vital signs (such as heart rates and respiration rates) remotely and continuously without touching the patients, for example, can be an invaluable tool for physicians who need to make rapid life-and-death decisions. Such a system would also be an effective tool to help physicians and patients make better informed decisions when viewing a patient’s long-term monitored data. Therefore, there has been a large increase in research activities to develop a system that can monitor a patient’s vital signs and quickly transmit the information to healthcare professionals. Radio-Frequency (RF) Non-contact vital signs (NCVS) monitoring system are particularly attractive for long term vital signs monitoring because there are no wires, electrodes, wearable devices, nor contact-based sensors for the subjects to worry about. Approach: In this paper, we will provide a brief review on some latest development on NCVS sensors, and also compare them against a novel phased-array Doppler-based RF non-contact NCVS biosensor system we have built in our RF-SoC Lab. To determine the accuracy of our NCVS sensor, the heart rate measurements from our NCVS system are compared against an external contact-based piezoelectric finger sensor as a reference. Objective: In some of our previous works, the NCVS sensor performance was tested within a clutter-free anechoic chamber inside our Lab to mitigate the environmental clutters. To examine the performance of our NCVS sensor in a more practical setting, most tests here were performed within the typical Herman-Miller type office cubicle setting, inside a section of our Lab. Additionally, we will detail the measurement data to demonstrate the feasibility of long-term noncontact vital signs monitoring. Conclusion: The measured data strongly suggests that our latest phased array NCVS system should be able to perform long-term vital signs monitoring, especially for situations where the subject is sleeping and there is not expected to have hectic movements nearby. Recommendation: Our phased-array NCVS biosensor system appears to be quite robust and attractive. We will be performing several 24-hours tests to quantitatively analyze the effects of the background noise to long-term vital signs monitoring in office cubicle setting, and report our findings on these important topics in the near future. In the future, we also plan to continue to perform long-term NCVS monitoring on subjects during their sleep next for potential applications on sleep apnea and sudden cardiac arrest (SCA) patients.

Manipulator Tactile Telepresence Research Based on one Type Pressure-Sensitive Sensor

A pressure-sensitive tactile sensor is with simple structure, well tolerated material and reliable to meet a variety of applications, particularly easy to realize the structure of the finger sensor that has a biomimetic properties. The characteristics of information collection, and the corresponding supporting technology on tactile reproduction has researched, in order to make the operator aware of the effective electric haptic, and does not appear tinglin. In addition to control the dynamic range of stimulating current, also the waveform, frequency and complete telepresence grasp process are studied.

Use of the Nexfin™ device to detect acute arterial pressure variations during anaesthesia induction

Standard non-invasive arterial pressure (AP) measurements are discontinuous. By providing non-invasive beat-to-beat AP measurements, Nexfin™ might limit duration of intraoperative hypotension and hypertension. We assessed the ability of Nexfin™ to detect AP variations by comparing its trending ability with invasive AP monitoring. Thirty-one subjects undergoing elective surgery under general anaesthesia were included. During induction, simultaneous pairs of AP measurements were collected every 5 s from the Nexfin™ finger sensor and a homolateral radial artery catheter. Magnitude and time lags of AP variations from baseline to nadir and peak were calculated for both methods. Concordance analysis was performed by the Bland-Altman method (for comparison of repeated measures when appropriate). Nexfin™ detected 100% of AP changes with the median delays of 0 s (-13 to 7) and 0 s (-5 to 12) for nadir and peak, respectively. Bias [limits of agreement (LOA)] of systolic AP (SAP) variations was -0.5 mm Hg (-31.2 to 30.2) and -9.4 mm Hg (-31.3 to 12.6) from baseline to nadir and from baseline to peak, respectively. For 3479 analysed paired measurements, bias was -3.8 and -8.8 mm Hg for SAP and diastolic AP, with LOA of (-36.0 to 28.5) and (-29.8 to 12.3), respectively. Nexfin™ detects AP variations accurately and can be a useful warning device during anaesthesia. However, it is not interchangeable with invasive monitoring, given the large LOA between the two measurements. NCT01658631.

An Institutional Case Study: Emotion Regulation with HeartMath at Santa Cruz County Children's Mental Health

This case study from Santa Cruz County Children's Mental Health Agency (CMH), California, reviews the use of measurement of heart rate variability (HRV) to enhance emotional regulation of patients. CMH serves seriously emotionally disturbed youths, many of whom have been separated from their parents for a prolonged period or have been vulnerable without the consistent presence of their caregivers. In this study, the HRV pattern was calculated as high coherence, medium coherence, or low coherence. According to Thurber et al, heart rhythm coherence “is experienced as a calm, balanced, yet energized and responsive state that is conducive to everyday functioning and interaction, including the performance of tasks requiring mental acuity, focus, problem solving and decision making, as well as physical activity and coordination.”1(p39) In the HeartMath program, there was a game in which high coherence was rewarded with a rainbow that dropped coins into a vessel. When coherence was low, the rainbow and coins disappeared until coherence was reached again. We measured HRV using a finger or ear sensor in individual sessions using a computer-based program from HeartMath Institute, Boulder Creek, California.After juvenile offenders overcame their initial fear of being hooked up to a potential lie detector, I instructed them in “Quick Coherence”1 and asked them to imagine breathing into the area of their heart. The participants created a library of positive feelings, thoughts, and memories on which they could focus. After a period of positive focus and rhythmic breathing, the clients were often able to move into medium or high coherence. In this state, they noticed that they felt calmer. I explained that they could use this tool to improve their mood. I also practiced alongside the youths in order to demonstrate the technique.The detained youths learned quickly, requested repeated sessions, and learned to combine breathing with recalling the good people, places, foods, and feelings in their lives that sustained them. We could also decrease coherence through the use of negative words such as “loss of privileges” on their side or “pay cut” on mine and then move back to coherence with suggestions of positive mental images.