Design and Evaluation of Digital Filters for Non-Contact Measuring of HRV using Medical Radar and Its Application in Bedside Patient Monitoring System.

A non-contact bedside monitoring system using medical radar is expected to be applied to clinical fields. Our previous studies have developed a monitoring system based on medical radar for measuring respiratory rate (RR) and heart rate (HR). Heart rate variability (HRV), which is essentially implemented in advanced monitoring system, such as prognosis prediction, is a more challenging biological information than the RR and HR. In this study, we designed a HRV measurement filter and proposed a method to evaluate the optimal cardiac signal extraction filter for HRV measurement. Because the cardiac component in the radar signal is much smaller than the respiratory component, it is necessary to extract the cardiac element from the radar output signal using digital filters. It depends on the characteristics of the filter whether the HRV information is kept in the extracted cardiac signal or not. A cardiac signal extraction filter that is not distorted in the time domain and does not miss the cardiac component must be adopted. Therefore, we focused on evaluating the interval between the R-peak of the electrocardiogram (ECG) and the radar-cardio peak of the cardiac signal measured by radar (R-radar interval). This is based on the fact that the time between heart depolarization and ventricular contraction is measured as the R-radar interval. A band-pass filter (BPF) with several bandwidths and a nonlinear filter, locally projective adaptive signal separation (LoPASS), were analyzed and compared. The optimal filter was quantitatively evaluated by analyzing the distribution and standard deviation of the R-radar intervals. The performance of this monitoring system was evaluated in elderly patient at the Yokohama Hospital, Japan.

Non-contact heart rate variability monitoring using Doppler radars located beneath bed mattress: a case report.

BACKGROUND: Heart rate variability (HRV) has been investigated previously in autonomic nervous system-related clinical settings. In these settings, HRV is determined by the time-series heartbeat peak-to-peak intervals using electrocardiography (ECG). To reduce patient discomfort, we designed a Doppler radar-based autonomic nervous activity monitoring system (ANMS) that allows cardiopulmonary monitoring without using ECG electrodes or spirometry monitoring. CASE SUMMARY: Using our non-contact ANMS, we observed a bedridden 80-year-old female patient with terminal phase sepsis developed the daytime Cheyne-Stokes respiration (CSR) associated with the attenuation of the low frequency (LF) and high frequency (HF) of HRV components 20 days prior to her death. The patient developed a marked linear decrease in the LF and the HF of HRV components for over 3 days in a row. Furthermore, after the decrease both the LF and the HF showed low and linear values. Around the intersection of the two lines, the decreasing LF and HF lines and the constant LF and HF lines, the ANMS automatically detected the daytime CSR pathogenesis. The attenuation rate of HF (1340 ms2/day) was higher than that of LF (956 ms2/day). Heart rate increased by ∼10 b.p.m. during these 3 days. DISCUSSION: We detected CSR-associated LF and HF attenuation in a patient with terminal phase sepsis using our ANMS. The proposed system without lead appears promising for future applications in clinical settings, such as remote cardiac monitoring of patients with heart failure at home or in long-term acute care facilities.

Twenty-four-hour continuous and remote monitoring of respiratory rate using a medical radar system for the early detection of pneumonia in symptomatic elderly bedridden hospitalized patients.

Respiratory rate is often measured manually and discontinuously by counting of chest wall movements in routine clinical practice. We introduce a novel approach to investigate respiration dynamics using a noncontact medical radar system for identifying patient at risk of infection. The system enables early detection of pneumonia in bedridden hospitalized patients.

Multiple Vital-Sign-Based Infection Screening Outperforms Thermography Independent of the Classification Algorithm.

GOAL: Thermography-based infection screening at international airports plays an important role in the prevention of pandemics. However, studies show that thermography suffers from low sensitivity and specificity. To achieve higher screening accuracy, we developed a screening system based on the acquisition of multiple vital-signs. This multimodal approach increases accuracy, but introduces the need for sophisticated classification methods. This paper presents a comprehensive analysis of the multimodal approach to infection screening from a machine learning perspective. METHODS: We conduct an empirical study applying six classification algorithms to measurements from the multimodal screening system and comparing their performance among each other, as well as to the performance of thermography. In addition, we provide an information theoretic view on the use of multiple vital-signs for infection screening. The classification methods are tested using the same clinical data, which has been analyzed in our previous study using linear discriminant analysis. A total of 92 subjects were recruited for influenza screening using the system, consisting of 57 inpatients diagnosed to have seasonal influenza and 35 healthy controls. RESULTS: Our study revealed that the multimodal screening system reduces the misclassification rate by more than 50% compared to thermography. At the same time, none of the multimodal classifiers needed more than 6 ms for classification, which is negligible for practical purposes. CONCLUSION: Among the tested classifiers k-nearest neighbors, support vector machine and quadratic discriminant analysis achieved the highest cross-validated sensitivity score of 93%. SIGNIFICANCE: Multimodal infection screening might be able to address the shortcomings of thermography.

Lemierre's Syndrome Associated with Periodontal Injury-derived Odontogenic Infection that Did Not Respond to Meropenem.

A 33-year-old previously healthy man injured his gums and subsequently developed dyspnea and fever. A chest X-ray showed nodules and infiltrates in both lungs, and the patient was initially diagnosed with pneumonia and administered meropenem hydrate, although his symptoms did not improve. A blood culture identified Fusobacterium necrophorum, and thrombophlebitis in the internal jugular vein of the neck was observed on computed tomography and ultrasound scans. We replaced the meropenem with clindamycin, sulbactam/ampicillin and metronidazole, and the patient's symptoms improved.

An infectious disease/fever screening radar system which stratifies higher-risk patients within ten seconds using a neural network and the fuzzy grouping method.

OBJECTIVES: To classify higher-risk influenza patients within 10 s, we developed an infectious disease and fever screening radar system. METHODS: The system screens infected patients based on vital signs, i.e., respiration rate measured by a radar, heart rate by a finger-tip photo-reflector, and facial temperature by a thermography. The system segregates subjects into higher-risk influenza (HR-I) group, lower-risk influenza (LR-I) group, and non-influenza (Non-I) group using a neural network and fuzzy clustering method (FCM). We conducted influenza screening for 35 seasonal influenza patients and 48 normal control subjects at the Japan Self-Defense Force Central Hospital. Pulse oximetry oxygen saturation (SpO2) was measured as a reference. RESULTS: The system classified 17 subjects into HR-I group, 26 into LR-I group, and 40 into Non-I group. Ten out of the 17 HR-I subjects indicated SpO2 <96%, whereas only two out of the 26 LR-I subjects showed SpO2 <96%. The chi-squared test revealed a significant difference in the ratio of subjects showed SpO2 <96% between HR-I and LR-I group (p < 0.001). There were zero and nine normal control subjects in HR-I and LR-I groups, respectively, and there was one influenza patient in Non-I group. CONCLUSIONS: The combination of neural network and FCM achieved efficient detection of higher-risk influenza patients who indicated SpO2 96% within 10 s.

Fever screening of seasonal influenza patients using a cost-effective thermopile array with small pixels for close-range thermometry.

OBJECTIVE: Infrared thermography systems have been used for fever screening at many airports since the outbreak of severe acute respiratory syndrome (SARS) in 2003. However, many of these systems are expensive and non-portable. Therefore, we developed a cost-effective and compact (2.9 × 5.8 × 2.0 cm) thermopile array for fever screening of patients with infectious diseases in the clinical setting. METHODS: The array was created with small pixels (48 × 47 = 2256 pixels) fabricated on a silicon wafer using microelectromechanical systems technology. We tested this array on 155 febrile and afebrile patients (35.4°C ≤ axillary temperature ≤ 39.3°C) with seasonal influenza at the Japan Self-Defense Forces Central Hospital. RESULTS: The maximum facial temperature, measured by the array at 0.3 m from the subject, exhibited a positive correlation with axillary temperature measured using a contact-type thermometer (r = 0.71, p < 0.01). The sensitivity and specificity of the thermopile array in identifying the febrile subjects were 80.5% and 93.3%, respectively, setting the threshold cut-off of maximum facial temperature at an appropriate value. CONCLUSIONS: Our cost-effective thermopile array appears promising for future close-range fever screening of patients with infectious diseases at primary care doctor clinics, health care centers, and quarantine stations in developing and developed countries.

Design an easy-to-use infection screening system for non-contact monitoring of vital-signs to prevent the spread of pandemic diseases.

The outbreak of infectious diseases such as influenza, dengue fever, and severe acute respiratory syndrome (SARS) are threatening the global health. Especially, developing countries in the South-East Asia region have been at serious risk. Rapid and highly reliable screening of infection is urgently needed during the epidemic season at mass gathering places, such as airport quarantine facilities, public health centers, and hospital outpatients units, etc. To meet this need, our research group is currently developing a multiple vital-signs based infection screening system that can perform human medical inspections within 15 seconds. This system remotely monitors facial temperature, heart and respiration rates using a thermopile array and a 24-GHz microwave radar, respectively. In this work, we redesigned our previous system to make a higher performance with a user-friendly interface. Moreover, the system newly included a multivariable logistic regression model (MLRM) to determine the possibility of infection. We tested the system on 34 seasonal influenza patients and 35 normal control subjects at the Japan Self-Defense Forces Central Hospital. The sensitivity and specificity of the screening system using the MLRM were 85.3% and 88.6%, respectively.

Development of an infection screening system for entry inspection at airport quarantine stations using ear temperature, heart and respiration rates.

After the outbreak of severe acute respiratory syndrome (SARS) in 2003, many international airport quarantine stations conducted fever-based screening to identify infected passengers using infrared thermography for preventing global pandemics. Due to environmental factors affecting measurement of facial skin temperature with thermography, some previous studies revealed the limits of authenticity in detecting infectious symptoms. In order to implement more strict entry screening in the epidemic seasons of emerging infectious diseases, we developed an infection screening system for airport quarantines using multi-parameter vital signs. This system can automatically detect infected individuals within several tens of seconds by a neural-network-based discriminant function using measured vital signs, i.e., heart rate obtained by a reflective photo sensor, respiration rate determined by a 10-GHz non-contact respiration radar, and the ear temperature monitored by a thermography. In this paper, to reduce the environmental effects on thermography measurement, we adopted the ear temperature as a new screening indicator instead of facial skin. We tested the system on 13 influenza patients and 33 normal subjects. The sensitivity of the infection screening system in detecting influenza were 92.3%, which was higher than the sensitivity reported in our previous paper (88.0%) with average facial skin temperature.

Effective Treatment of Intestinal Behçet's Disease with Long-Term, Low-Dose Clarithromycin.

A 51-year-old man was referred for body weight loss and lower right abdominal pain. Total colonoscopy revealed discrete and round ulceration at the ileocecal valve, and he was diagnosed with intestinal Behçet's disease (BD). By treatment with glucocorticoid, colchicine and salazosulfapyridine, the symptoms and ulceration were improved, but cessation of glucocorticoid resulted in relapse of ulceration at the terminal ileum. Long-term, low-dose treatment with clarithromycin (CAM) was implemented for chronic respiratory infections. Furthermore, we expected that this CAM treatment would also be effective in BD. During this long-term, low-dose treatment with CAM, discrete ulceration at the terminal ileum was never revealed by follow-up total colonoscopy once or twice per year for 7 years. No reports have described the effectiveness of this treatment in patients with intestinal BD; however, we confirm that long-term treatment with low-dose CAM might have clinical benefits for patients with intestinal BD.

Mobile and accurate detection system for infection by the 2009 pandemic influenza A (H1N1) virus with a pocket-warmer reverse-transcriptase loop-mediated isothermal amplification.

The 2009 pandemic H1N1 influenza A virus spread quickly worldwide in 2009. Since most of the fatal cases were reported in developing countries, rapid and accurate diagnosis methods that are usable in poorly equipped laboratories are necessary. In this study, a mobile detection system for the 2009 H1N1 influenza A virus was developed using a reverse-transcriptase loop-mediated isothermal amplification (RT-LAMP) kit with a disposable pocket-warmer as a heating device (designated as pwRT-LAMP). The pwRT-LAMP can detect as few as 100 copies of the virus--which is nearly as sensitive as real-time reverse-transcription polymerase chain reaction (RT-PCR)--and does not cross-react with RNA of seasonal influenza viruses. To evaluate the usefulness of the pwRT-LAMP system, nasal swab samples were collected from 56 patients with flu-like symptoms and were tested. Real-time RT-PCR confirmed that the 2009 H1N1 influenza A virus was present in 27 of the 56 samples. Of these 27 positive samples, QuickVue Influenza A+B immunochromatography detected the virus in only 11 samples (11/27; 40.7%), whereas the pwRT-LAMP system detected the virus in 26 of the 56 samples (26/27 of the positive samples; 96.3%). These findings indicate that the mobile pwRT-LAMP system is an accurate diagnostic system for the 2009 H1N1 influenza A virus, and has great potential utility in diagnosing future influenza pandemics.

A successfully treated case of hyperosmolar hyperglycemic state complicated with rhabdomyolysis, acute kidney injury, and ischemic colitis.

A 48-year-old Japanese male was admitted to our hospital due to hyperosmolar hyperglycemic state (HHS), combined with rhabdomyolysis and acute kidney injury. His blood sugar levels were gradually decreased by fluid resuscitation and insulin infusion; however, his renal function worsened, and he developed bloody stools. He required continuous hemodiafiltration to improve his hemodynamics. As colonoscopy revealed longitudinal ulcers, ischemic colitis was diagnosed. We treated him conservatively at first, but when we found the ulceration of the sigmoid colon had penetrated the mesenterium, colectomy was indicated. After surgery, his general condition improved. Careful monitoring of complications related to HHS is important.

A novel screening method for influenza patients using a newly developed non-contact screening system.

OBJECTIVES: In places of mass gathering, rapid infection screening prior to definite diagnosis is vital during the epidemic season of a novel influenza. In order to assess the possibility of clinical application of a newly developed non-contact infection screening system, we conducted screening for influenza patients. MATERIALS AND METHODS: The system is operated by a screening program via a linear discriminant analysis using non-contact derived variables, i.e., palmar pulse derived from a laser Doppler blood-flow meter, respiration rate determined by a 10-GHz microwave radar, and average facial temperature measured by thermography. The system was tested on 57 seasonal influenza (2008-2009) patients (35.7 degrees C < or = body temperature < or = 38.3 degrees C, 19-40 years) and 35 normal control subjects (35.5 degrees C < or = body temperature < or = 36.9 degrees C, 21-35 years) at the Japan Self-defense Forces Central Hospital. RESULTS: A significant linear discriminant function (p < 0.001) was determined to distinguish the influenza group from the control group (Mahalanobis D-square = 6.5, classification error rate > 10%). The system had a positive predictive value (PPV) of 93%, which is higher than the PPV value (PPV < or = 65.4%) reported in the recent summary of studies using only thermography performed mainly in hospitals. CONCLUSIONS: The proposed system appears promising for application in accurate screening for influenza patients at places of mass gathering.

A case of incidentally detected IgG4-related sclerosing disease involving inflammatory abdominal aortic aneurysm and autoimmune pancreatitis.

A 59-year-old asymptomatic man was incidentally found to have a periaortic mass and an elevated serum amylase level during his medical check-up. Additional findings, such as infiltration of immunoglobulin G4 (IgG4)-producing plasma cells in the mass lesion, elevation of serum IgG4 (1000 mg/dl), and pancreatic duct narrowing as evidenced on a magnetic resonance cholangiopancreatography scan, confirmed the diagnosis as retroperitoneal fibrosis complicated with autoimmune pancreatitis. The patient responded favorably to steroid treatment before the appearance of symptoms.