Smart vest for respiratory rate monitoring of COPD patients based on non-contact capacitive sensing

In this paper, a first approach to the design of a portable device for non-contact monitoring of respiratory rate by capacitive sensing is presented. The sensing system is integrated into a smart vest for an untethered, low-cost and comfortable breathing monitoring of Chronic Obstructive Pulmonary Disease (COPD) patients during the rest period between respiratory rehabilitation exercises at home. To provide an extensible solution to the remote monitoring using this sensor and other devices, the design and preliminary development of an e-Health platform based on the Internet of Medical Things (IoMT) paradigm is also presented. In order to validate the proposed solution, two quasi-experimental studies have been developed, comparing the estimations with respect to the golden standard. In a first study with healthy subjects, the mean value of the respiratory rate error, the standard deviation of the error and the correlation coefficient were 0.01 breaths per minute (bpm), 0.97 bpm and 0.995 (p < 0.00001), respectively. In a second study with COPD patients, the values were -0.14 bpm, 0.28 bpm and 0.9988 (p < 0.0000001), respectively. The results for the rest period show the technical and functional feasibility of the prototype and serve as a preliminary validation of the device for respiratory rate monitoring of patients with COPD.Ministerio de Ciencia e Innovación PI15/00306Ministerio de Ciencia e Innovación DTS15/00195Junta de Andalucía PI-0010-2013Junta de Andalucía PI-0041-2014Junta de Andalucía PIN-0394-201

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 192

This bibliography lists 247 reports, articles, and other documents introduced into the NASA scientific and technical information system in March 1979

Advanced sensors technology survey

This project assesses the state-of-the-art in advanced or 'smart' sensors technology for NASA Life Sciences research applications with an emphasis on those sensors with potential applications on the space station freedom (SSF). The objectives are: (1) to conduct literature reviews on relevant advanced sensor technology; (2) to interview various scientists and engineers in industry, academia, and government who are knowledgeable on this topic; (3) to provide viewpoints and opinions regarding the potential applications of this technology on the SSF; and (4) to provide summary charts of relevant technologies and centers where these technologies are being developed

Pulse Signal System: Sensing, Data Acquisition and Body Area Network

Heart rate variability (HRV) is an important physiological signal of the human body, which can serve as a useful biomarker for the cardiovascular health status of an individual. There are many methods to measure the HRV using electrical devices, such as ECG and PPG etc. This work presents a novel HRV detection method which is based on pressure detection on the human wrist. This method has been compared with existing HRV detection methods. In this work, the proposed system for HRV detection is based on polyvinylidene difluoride (PVDF) sensor, which can measure tiny pressure on its surface. Three PVDF sensors are mounted on the wrist, and a three-channel conditioning circuit is used to amplify signals generated by the sensors. An analog-to-digital converter and Arduino microcontroller are used to sample and process the signal. Based on the obtained signals, the HRV can be processed and detected by the proposed PVDF-sensor-based system. Another contribution of this work is in designing a wireless body area network (WBAN) to transmit data acquired on the human body. This WBAN combines two different wireless network protocols, for both efficient power consumption and data rate. Bluetooth Low Energy protocol is used for transmitting data from the microcontroller to a personal device, and Wi-Fi is used to send data to other terminals. This provides the potential for remote HRV signal monitoring. A dataset consisting of two subjects was used to experimentally validate the proposed system design and signal processing method. ECG signals are acquired from subjects with wrist pulse signals for comparison as standard signal. The waveforms of ECG signals and wrist pulse signals are compared and HRV values are calculated from these two signals separately. The result shows that HRV calculated by wrist pulse has low error rate. A test of movement effect shows the sensor can resist mild motions of wrist. Some future improvements of system design and further signal processing methods are also discussed in the last chapter

Wireless Tissue Palpation for Intraoperative Detection of Lumps in the Soft Tissue

In an open surgery, identification of precise margins for curative tissue resection is performed by manual palpation. This is not the case for minimally invasive and robotic procedures, where tactile feedback is either distorted or not available. In this paper, we introduce the concept of intraoperative wireless tissue palpation. The wireless palpation probe (WPP) is a cylindrical device (15 mm in diameter, 60 mm in length) that can be deployed through a trocar incision and directly controlled by the surgeon to create a volumetric stiffness distribution map of the region of interest. This map can then be used to guide the tissue resection to minimize healthy tissue loss. The wireless operation prevents the need for a dedicated port and reduces the chance of instrument clashing in the operating field. The WPP is able to measure in real time the indentation pressure with a sensitivity of 34 Pa, the indentation depth with an accuracy of 0.68 mm, and the probe position with a maximum error of 11.3 mm in a tridimensional workspace. The WPP was assessed on the benchtop in detecting the local stiffness of two different silicone tissue simulators (elastic modulus ranging from 45 to 220 kPa), showing a maximum relative error below 5%. Then, in vivo trials were aimed to identify an agar-gel lump injected into a porcine liver and to assess the device usability within the frame of a laparoscopic procedure. The stiffness map created intraoperatively by the WPP was compared with a map generated ex vivo by a standard uniaxial material tester, showing less than 8% local stiffness error at the site of the lump

Wireless Point-of-Care Platform With Screen-Printed Sensors for Biomarkers Detection

Measurement systems for early and reliable detection of degenerative diseases, such as Alzheimer's disease (AD), are extremely important in clinical diagnosis. Among these, biochemical assays represent a commonly used method to distinguish patients from healthy population thanks to the sensitive recognition of specific biomarkers in biological fluids. In order to overcome actual limitations of these techniques in term of cost, standardization, and sensitivity, this study aimed to realize a low-cost highly sensitive portable point-of-care (PoC) testing system based on screen-printed electrochemical sensors. The development of the platform specifically included both the design of the sensing probe and the electronic circuit devoted to condition and acquires the transduced electric signal. The designed circuit was implemented in a printed circuit board and interfaced to a wireless system based on bluetooth data transmission in order to improve the portability of the proposed solution. Preliminary results were obtained by using controlled concentrations of electrolytic solutions and calibrating the sensors for antibodies and for a well-known protein (i.e., interleukin 8) quantified by anodic stripping voltammetry (ASV). Findings from ASV measurements showed a sensitivity of 38 μA/(ng/ml) with a tested range from 1.25 to 20 ng/ml, with a limit of detection of 2 ng/ml. Further investigation will include the validation of this PoC device by testing the concentration of a specific p53 protein isoform, which was recently identified to early correlate to AD development