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Sensing for Biomedical Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".

Deadline for manuscript submissions: closed (31 July 2022) | Viewed by 38060

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Department of Industrial Engineering, University of Padova, 35131 Padova, Italy
Interests: CAD modeling; reverse engineering; additive manufacturing; computer vision; image processing; watermarking; image forensics; bioengineering
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Special Issue Information

Dear Colleagues,

Rapid advancements in sensor and medical imaging technologies in recent years have facilitated the widespread use of both more accurate diagnosis and personalized medical devices and treatments. Many kinds of sensors and systems have been used in disease detection, medical simulation, patient-specific surgical tools, and medical device design pipelines, as well as home monitoring or activity recognition.

This Special Issue solicits review and original articles on state-of-the-art sensors, multiple sensor systems, and methodologies for metrological characterization of biomedical applications. A wide range of topics are covered, including but not limited to:

  • Anatomical acquisition systems;
  • 3D depth camera-based sensor systems;
  • Computer-aided design of personalized medical devices and surgical tools;
  • Medical imaging systems;
  • Methodologies for the metrological characterization of sensors for biomedical applications;
  • Optical sensors systems;
  • Real time monitoring of anatomical parts;
  • Signal processing and image processing;
  • Virtual and physical simulation and planning in surgery;
  • Wearable and implantable sensors and devices.

Dr. Francesca Uccheddu
Guest Editor

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Published Papers (8 papers)

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Research

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11 pages, 1394 KiB  
Article
Optical Identification of Parenteral Nutrition Solutions Exploiting Refractive Index Sensing
by Valentina Bello, Elisabetta Bodo and Sabina Merlo
Sensors 2022, 22(18), 6815; https://doi.org/10.3390/s22186815 - 8 Sep 2022
Cited by 2 | Viewed by 17313
Abstract
Parenteral artificial nutrition (PAN) is a lifesaving treatment for a large population of patients affected by different diseases, and it consists of intravenous injection of nutritive fluids by means of infusion pumps. Wrong PAN solutions are, unfortunately, often administered, thus threatening the patients’ [...] Read more.
Parenteral artificial nutrition (PAN) is a lifesaving treatment for a large population of patients affected by different diseases, and it consists of intravenous injection of nutritive fluids by means of infusion pumps. Wrong PAN solutions are, unfortunately, often administered, thus threatening the patients’ well-being. Here, we report an optofluidic label-free sensor that can distinguish PAN solutions on the basis of their volumetric refractive index (RI). In our system, a monochromatic light beam, generated by a laser diode, travels obliquely through a transparent, square-section polystyrene channel, is then back-reflected by a mirror, and finally exits the channel in a position that depends on the filling fluid RI. The displacement of the output light spot ΔXexperim is easily detected with a linear, 1-D position sensitive detector (PSD). We initially calibrated the sensor with water-glucose solutions demonstrating a sensitivity S = ΔXexperimn = 13,960 µm/RIU. We then clearly distinguished six commercial PAN solutions, commonly administered to patients. To the best of our knowledge, this is the first reported healthcare sensing platform for remote contactless recognition of PAN fluids, which could be inserted into infusion pumps to improve treatment safety, by checking the compliance to the prescription of the fluid actually delivered to the patient. Full article
(This article belongs to the Special Issue Sensing for Biomedical Applications)
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18 pages, 5278 KiB  
Article
Whitening Technique Based on Gram–Schmidt Orthogonalization for Motor Imagery Classification of Brain–Computer Interface Applications
by Hojong Choi, Junghun Park and Yeon-Mo Yang
Sensors 2022, 22(16), 6042; https://doi.org/10.3390/s22166042 - 12 Aug 2022
Cited by 7 | Viewed by 1967
Abstract
A novel whitening technique for motor imagery (MI) classification is proposed to reduce the accuracy variance of brain–computer interfaces (BCIs). This method is intended to improve the electroencephalogram eigenface analysis performance for the MI classification of BCIs. In BCI classification, the variance of [...] Read more.
A novel whitening technique for motor imagery (MI) classification is proposed to reduce the accuracy variance of brain–computer interfaces (BCIs). This method is intended to improve the electroencephalogram eigenface analysis performance for the MI classification of BCIs. In BCI classification, the variance of the accuracy among subjects is sensitive to the accuracy itself for superior classification results. Hence, with the help of Gram–Schmidt orthogonalization, we propose a BCI channel whitening (BCICW) scheme to minimize the variance among subjects. The newly proposed BCICW method improved the variance of the MI classification in real data. To validate and verify the proposed scheme, we performed an experiment on the BCI competition 3 dataset IIIa (D3D3a) and the BCI competition 4 dataset IIa (D4D2a) using the MATLAB simulation tool. The variance data when using the proposed BCICW method based on Gram–Schmidt orthogonalization was much lower (11.21) than that when using the EFA method (58.33) for D3D3a and decreased from (17.48) to (9.38) for D4D2a. Therefore, the proposed method could be effective for MI classification of BCI applications. Full article
(This article belongs to the Special Issue Sensing for Biomedical Applications)
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18 pages, 16217 KiB  
Article
Towards Multimodal Equipment to Help in the Diagnosis of COVID-19 Using Machine Learning Algorithms
by Ana Cecilia Villa-Parra, Ismael Criollo, Carlos Valadão, Leticia Silva, Yves Coelho, Lucas Lampier, Luara Rangel, Garima Sharma, Denis Delisle-Rodríguez, John Calle-Siguencia, Fernando Urgiles-Ortiz, Camilo Díaz, Eliete Caldeira, Sridhar Krishnan and Teodiano Bastos-Filho
Sensors 2022, 22(12), 4341; https://doi.org/10.3390/s22124341 - 8 Jun 2022
Cited by 6 | Viewed by 2508
Abstract
COVID-19 occurs due to infection through respiratory droplets containing the SARS-CoV-2 virus, which are released when someone sneezes, coughs, or talks. The gold-standard exam to detect the virus is Real-Time Polymerase Chain Reaction (RT-PCR); however, this is an expensive test and may require [...] Read more.
COVID-19 occurs due to infection through respiratory droplets containing the SARS-CoV-2 virus, which are released when someone sneezes, coughs, or talks. The gold-standard exam to detect the virus is Real-Time Polymerase Chain Reaction (RT-PCR); however, this is an expensive test and may require up to 3 days after infection for a reliable result, and if there is high demand, the labs could be overwhelmed, which can cause significant delays in providing results. Biomedical data (oxygen saturation level—SpO2, body temperature, heart rate, and cough) are acquired from individuals and are used to help infer infection by COVID-19, using machine learning algorithms. The goal of this study is to introduce the Integrated Portable Medical Assistant (IPMA), which is a multimodal piece of equipment that can collect biomedical data, such as oxygen saturation level, body temperature, heart rate, and cough sound, and helps infer the diagnosis of COVID-19 through machine learning algorithms. The IPMA has the capacity to store the biomedical data for continuous studies and can be used to infer other respiratory diseases. Quadratic kernel-free non-linear Support Vector Machine (QSVM) and Decision Tree (DT) were applied on three datasets with data of cough, speech, body temperature, heart rate, and SpO2, obtaining an Accuracy rate (ACC) and Area Under the Curve (AUC) of approximately up to 88.0% and 0.85, respectively, as well as an ACC up to 99% and AUC = 0.94, respectively, for COVID-19 infection inference. When applied to the data acquired with the IMPA, these algorithms achieved 100% accuracy. Regarding the easiness of using the equipment, 36 volunteers reported that the IPMA has a high usability, according to results from two metrics used for evaluation: System Usability Scale (SUS) and Post Study System Usability Questionnaire (PSSUQ), with scores of 85.5 and 1.41, respectively. In light of the worldwide needs for smart equipment to help fight the COVID-19 pandemic, this new equipment may help with the screening of COVID-19 through data collected from biomedical signals and cough sounds, as well as the use of machine learning algorithms. Full article
(This article belongs to the Special Issue Sensing for Biomedical Applications)
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18 pages, 2385 KiB  
Article
Using Acoustic Vibrations as a Method for Implant Insertion Assessment in Total Hip Arthroplasty
by Jonathan C. J. Wei, Willem H. A. Crezee, Hilda Jongeneel, Tobias S. A. De Haas, Wesley L. A. Kool, Bryan J. Blaauw, Jenny Dankelman and Tim Horeman
Sensors 2022, 22(4), 1609; https://doi.org/10.3390/s22041609 - 18 Feb 2022
Cited by 2 | Viewed by 2098
Abstract
The success of total hip arthroplasty depends on the experience of the surgeon, and one of the ways the surgeon currently determines the final implant insertion depth is to listen to the change in audible pitch of the hammering sound. We investigated the [...] Read more.
The success of total hip arthroplasty depends on the experience of the surgeon, and one of the ways the surgeon currently determines the final implant insertion depth is to listen to the change in audible pitch of the hammering sound. We investigated the use of vibration emissions as a novel method for insertion quality assessment. A non-invasive contact microphone-based measurement system for insertion depth estimation, fixation and fracture detection was developed using a simplified in vitro bone/implant (n = 5). A total of 2583 audio recordings were analyzed in vitro to obtain energy spectral density functions. Out of the four main resonant peaks under in vitro conditions, broach insertion depth statistically correlates to increasing 3rd and 4th peak frequencies. Degree of fixation was also observed as higher goodness of fit (0.26–0.78 vs. 0.12–0.51 between two broach sizes, the latter undersized). Finally, however, the moment of fracture could not be predicted. A cadaveric in situ pilot study suggests comparable resonant frequencies in the same order of magnitudes with the bone model. Further understanding of the signal patterns are needed for an early warning system diagnostic system for imminent fractures, bone damage, improving accuracy and quality of future procedures. Full article
(This article belongs to the Special Issue Sensing for Biomedical Applications)
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13 pages, 3964 KiB  
Article
RGB-D-Based Method for Measuring the Angular Range of Hip and Knee Joints during Home Care Rehabilitation
by Francesca Uccheddu, Rocco Furferi, Lapo Governi and Monica Carfagni
Sensors 2022, 22(1), 184; https://doi.org/10.3390/s22010184 - 28 Dec 2021
Cited by 2 | Viewed by 2359
Abstract
Home-based rehabilitation is becoming a gold standard for patient who have undergone knee arthroplasty or full knee replacement, as it helps healthcare costs to be minimized. Nevertheless, there is a chance of increasing adverse health effects in case of home care, primarily due [...] Read more.
Home-based rehabilitation is becoming a gold standard for patient who have undergone knee arthroplasty or full knee replacement, as it helps healthcare costs to be minimized. Nevertheless, there is a chance of increasing adverse health effects in case of home care, primarily due to the patients’ lack of motivation and the doctors’ difficulty in carrying out rigorous supervision. The development of devices to assess the efficient recovery of the operated joint is highly valued both for the patient, who feels encouraged to perform the proper number of activities, and for the doctor, who can track him/her remotely. Accordingly, this paper introduces an interactive approach to angular range calculation of hip and knee joints based on the use of low-cost devices which can be operated at home. First, the patient’s body posture is estimated using a 2D acquisition method. Subsequently, the 3D posture is evaluated by using the depth information coming from an RGB-D sensor. Preliminary results show that the proposed method effectively overcomes many limitations by fusing the results obtained by the state-of-the-art robust 2D pose estimation algorithms with the 3D data of depth cameras by allowing the patient to be correctly tracked during rehabilitation exercises. Full article
(This article belongs to the Special Issue Sensing for Biomedical Applications)
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15 pages, 2100 KiB  
Article
Measurement of Ex Vivo Liver, Brain and Pancreas Thermal Properties as Function of Temperature
by Ahad Mohammadi, Leonardo Bianchi, Somayeh Asadi and Paola Saccomandi
Sensors 2021, 21(12), 4236; https://doi.org/10.3390/s21124236 - 21 Jun 2021
Cited by 44 | Viewed by 4431
Abstract
The ability to predict heat transfer during hyperthermal and ablative techniques for cancer treatment relies on understanding the thermal properties of biological tissue. In this work, the thermal properties of ex vivo liver, pancreas and brain tissues are reported as a function of [...] Read more.
The ability to predict heat transfer during hyperthermal and ablative techniques for cancer treatment relies on understanding the thermal properties of biological tissue. In this work, the thermal properties of ex vivo liver, pancreas and brain tissues are reported as a function of temperature. The thermal diffusivity, thermal conductivity and volumetric heat capacity of these tissues were measured in the temperature range from 22 to around 97 °C. Concerning the pancreas, a phase change occurred around 45 °C; therefore, its thermal properties were investigated only until this temperature. Results indicate that the thermal properties of the liver and brain have a non-linear relationship with temperature in the investigated range. In these tissues, the thermal properties were almost constant until 60 to 70 °C and then gradually changed until 92 °C. In particular, the thermal conductivity increased by 100% for the brain and 60% for the liver up to 92 °C, while thermal diffusivity increased by 90% and 40%, respectively. However, the heat capacity did not significantly change in this temperature range. The thermal conductivity and thermal diffusivity were dramatically increased from 92 to 97 °C, which seems to be due to water vaporization and state transition in the tissues. Moreover, the measurement uncertainty, determined at each temperature, increased after 92 °C. In the temperature range of 22 to 45 °C, the thermal properties of pancreatic tissue did not change significantly, in accordance with the results for the brain and liver. For the three tissues, the best fit curves are provided with regression analysis based on measured data to predict the tissue thermal behavior. These curves describe the temperature dependency of tissue thermal properties in a temperature range relevant for hyperthermia and ablation treatments and may help in constructing more accurate models of bioheat transfer for optimization and pre-planning of thermal procedures. Full article
(This article belongs to the Special Issue Sensing for Biomedical Applications)
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17 pages, 8381 KiB  
Article
Investigation of Microwave Ablation Process in Sweet Potatoes as Substitute Liver
by Muhammad Saad Khan, Michael Hawlitzki, Shadan Mofrad Taheri, Georg Rose, Bernd Schweizer and Andreas Brensing
Sensors 2021, 21(11), 3894; https://doi.org/10.3390/s21113894 - 4 Jun 2021
Viewed by 2666
Abstract
The microwave ablation technique to destroy cancer tissues in liver is practiced clinically and is the subject of ongoing research, e.g., ablation monitoring. For studies, liver tissue from cattle or pigs is often used as a substitute material. In this work, sweet potato [...] Read more.
The microwave ablation technique to destroy cancer tissues in liver is practiced clinically and is the subject of ongoing research, e.g., ablation monitoring. For studies, liver tissue from cattle or pigs is often used as a substitute material. In this work, sweet potato is presented as an alternative material for microwave ablation experiments in liver due to similar material properties. Sweet potatoes as a substitute for liver have the advantages of better handling, easy procurement and stable material properties over time for microwave ablation experiments. The dielectric constant and electrical conductivity of sweet potato are characterized for temperature variation with the help of high-temperature dielectric probe. Furthermore, a test setup is presented for microwave ablation experiments in which a bowtie slot antenna matched to sweet potato is placed on its surface to directly receive the microwave power from a self-developed microwave applicator inserted into a sweet potato 4 cm below the surface antenna. A high-power source was used to excite the microwave powers up to 80 W and a spectrum analyzer was used to measure the signal received by the surface antenna. The experiments were performed in an anechoic chamber for safety reasons. Power at 50 W and 80 W was stimulated for a maximum of 600 s at the 2.45 GHz ISM band in different sweet potato experiments. A correlation is found between the power received by the surface antenna and rise of temperature inside sweet potato; relative received power drops from 1 at 76 C to 0.6 at 88 C (max. temperature) represents a 40% relative change in a 50 W microwave ablation experiment. The received power envelope at the surface antenna is between 10 mW and 32 mW during 50 W microwave ablation. Other important results for 10 min, 80 W microwave ablation include: a maximum ablation zone short axis diameter of 4.5 cm and a maximum ablation temperature reached at 99 C, 3 mm away from the applicator’s slot. The results are compared with the state of the art in microwave ablation in animal liver. The dielectric constant and electrical conductivity evolution of sweet potato with rising temperature is comparable to animal liver in 50–60 C range. The reflection loss of self-developed applicator in sweet potato is below 15 dB which is equal to reflection loss in liver experiments for 600 s. The temperature rise for the first 90 s in sweet potato is 76 C as compared to 73 C in liver with 50 W microwave ablation. Similarly, with 80–75 W microwave ablation, for the first 60 s, the temperature is 98 C in sweet potato as compared to 100 C in liver. The ablation zone short-axis diameter after 600 s is 3.3 cm for 50 W microwave ablation in sweet potato as compared to 3.5 cm for 30 W microwave ablation in liver. The reasons for difference in microwave ablation results in sweet potato and animal liver are discussed. This is the first study to directly receive a signal from microwave applicator during a microwave ablation process with the help of a surface antenna. The work can be extended to multiple array antennas for microwave ablation monitoring. Full article
(This article belongs to the Special Issue Sensing for Biomedical Applications)
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Review

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22 pages, 2886 KiB  
Review
Clinical Progress and Optimization of Information Processing in Artificial Visual Prostheses
by Jing Wang, Rongfeng Zhao, Peitong Li, Zhiqiang Fang, Qianqian Li, Yanling Han, Ruyan Zhou and Yun Zhang
Sensors 2022, 22(17), 6544; https://doi.org/10.3390/s22176544 - 30 Aug 2022
Cited by 4 | Viewed by 2666
Abstract
Visual prostheses, used to assist in restoring functional vision to the visually impaired, convert captured external images into corresponding electrical stimulation patterns that are stimulated by implanted microelectrodes to induce phosphenes and eventually visual perception. Detecting and providing useful visual information to the [...] Read more.
Visual prostheses, used to assist in restoring functional vision to the visually impaired, convert captured external images into corresponding electrical stimulation patterns that are stimulated by implanted microelectrodes to induce phosphenes and eventually visual perception. Detecting and providing useful visual information to the prosthesis wearer under limited artificial vision has been an important concern in the field of visual prosthesis. Along with the development of prosthetic device design and stimulus encoding methods, researchers have explored the possibility of the application of computer vision by simulating visual perception under prosthetic vision. Effective image processing in computer vision is performed to optimize artificial visual information and improve the ability to restore various important visual functions in implant recipients, allowing them to better achieve their daily demands. This paper first reviews the recent clinical implantation of different types of visual prostheses, summarizes the artificial visual perception of implant recipients, and especially focuses on its irregularities, such as dropout and distorted phosphenes. Then, the important aspects of computer vision in the optimization of visual information processing are reviewed, and the possibilities and shortcomings of these solutions are discussed. Ultimately, the development direction and emphasis issues for improving the performance of visual prosthesis devices are summarized. Full article
(This article belongs to the Special Issue Sensing for Biomedical Applications)
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