Giovanni Saggio | University of Rome Tor Vergata (original) (raw)

Papers by Giovanni Saggio

SN Computer Science , 2024

Current technologies allow acquiring whatever amount of data (even big data), from whatever syste... more Current technologies allow acquiring whatever amount of data (even big data), from whatever system (object, component, mechanism, network, implant, machinery, structure, asset, etc.), during whatever time lapse (secs, hours, weeks, years). Therefore, potentially it is possible to fully characterize any system for any time we need, with the possible consequence of creating a virtual copy, namely the digital twin (DT) of the system. When technology of DT meets an augmented reality scenario, the augmented digital twin (ADT) arises, when DT meets an artificial intelligence environment, the intelligent digital twin (IDT) arises. DTs, ADTs and IDTs are successfully adopted in electronics, mechanics, chemistry, manufacturing, science, sport, and more, but when adopted for the human body it comes out the human digital twin (HDT) or alternatively named virtual human simulator (VHS). When the VHS incorporates information from surroundings (other VHSs and environment), taking a cue from the particle-wave duality (the mix of matter and energy), we can name this super-VHS as the human digi-real duality (HDRD). This work is focused on defining the aforementioned acronyms, on evidencing their differences, advantages and successful case adoptions, but highlighting technology limits too, and on foreseeing new and intriguing possibilities.

Frontiers in Neurology, Jun 13, 2023

The analysis of vocal samples from patients with Parkinson's disease (PDP) can be relevant in sup... more The analysis of vocal samples from patients with Parkinson's disease (PDP) can be relevant in supporting early diagnosis and disease monitoring. Intriguingly, speech analysis embeds several complexities influenced by speaker characteristics (e.g., gender and language) and recording conditions (e.g., professional microphones or smartphones, supervised, or non-supervised data collection). Moreover, the set of vocal tasks performed, such as sustained phonation, reading text, or monologue, strongly a ects the speech dimension investigated, the feature extracted, and, as a consequence, the performance of the overall algorithm. Methods: We employed six datasets, including a cohort of Healthy Control (HC) participants and PDP from di erent nationalities (i.e., Italian, Spanish, Czech), recorded in variable scenarios through various devices (i.e., professional microphones and smartphones), and performing several speech exercises (i.e., vowel phonation, sentence repetition). Aiming to identify the e ectiveness of di erent vocal tasks and the trustworthiness of features independent of external co-factors such as language, gender, and data collection modality, we performed several intra-and inter-corpora statistical analyses. In addition, we compared the performance of di erent feature selection and classification models to evaluate the most robust and performing pipeline. Results: According to our results, the combined use of sustained phonation and sentence repetition should be preferred over a single exercise. As for the set of features, the Mel Frequency Cepstral Coe cients demonstrated to be among the most e ective parameters in discriminating between HC and PDP, also in the presence of heterogeneous languages and acquisition techniques. Conclusion: Even though preliminary, the results of this work can be exploited to define a speech protocol that can e ectively capture vocal alterations while minimizing the e ort required to the patient. Moreover, the statistical analysis identified a set of features minimally dependent on gender, language, and recording modalities. This discloses the feasibility of extensive cross-corpora tests to develop robust and reliable tools for disease monitoring and staging and PDP follow-up.

Springer eBooks, Jun 29, 2022

Hpb, Mar 1, 2019

stapler. Both, the right and left hepatic ducts were sutured side by side together to create a si... more stapler. Both, the right and left hepatic ducts were sutured side by side together to create a single bilioenteric anastomosis. Robotic hepaticojejunostomy was constructed with 2 running 3-0 V-Lock barbed sutures. A 10 Fr flat JP drain was placed dorsal to the hepaticojejunostomy. The patient tolerated the procedure well without intraoperative complications. Her postoperative recovery was uneventful. She was discharged home on postoperative day 4. Conclusion: The use of robotic technology in hepatobiliary operations is increasing but is still limited to a few specialized high-volume centers and in the hands of experts. Superior three-dimensional visualization and increased maneuverability with ease of suturing are only few of many advantages of the robotic technology.

Applied sciences, Apr 18, 2022

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

IEEE Journal of Biomedical and Health Informatics, Jul 1, 2022

OBJECTIVE In order to evaluate Parkinson disease patients response to therapeutic interventions, ... more OBJECTIVE In order to evaluate Parkinson disease patients response to therapeutic interventions, sources of information are mainly patient reports and clinicians assessment of motor functions. However, these sources can suffer from patients subjectivity and from inter/intra raters score variability. Our work aimed at determining the impact of wearable electronics and data analysis in objectifying the effectiveness of levodopa treatment. METHODS Seven motor tasks performed by thirty-six patients were measured by wearable electronics and related data were analyzed. This was at the time of therapy initiation (T0), and repeated after six (T1) and 12 months (T2). Wearable electronics consisted of inertial measurement units each equipped with 3-axis accelerometer and 3-axis gyroscope, while data analysis of ANOVA and Pearson correlation algorithms, in addition to a support vector machine (SVM) classification. RESULTS According to our findings, levodopa-based therapy alters the patients conditions in general, ameliorating something (e.g. bradykinesia), leaving unchanged others (e.g. tremor), but with poor correlation to the levodopa dose. CONCLUSION A technology-based approach can objectively assess levodopa-based therapy effectiveness. SIGNIFICANCE Novel devices can improve the accuracy of the assessment of motor function, by integrating the clinical evaluation and patient reports.

Springer eBooks, Jun 29, 2022

Bio-integrated wireless systems require to integrate electronic modules for bio-signal processing... more Bio-integrated wireless systems require to integrate electronic modules for bio-signal processing within a stretchable and soft skin-like device. The size and complexity of the PCB hosting circuitry cannot be separated from the design of the antenna used for the communication. Challenges arise when high frequencies are involved so that human body losses will deteriorate the radiation gain. This paper describes the design of a UHF-RFID epidermal antenna integrated with different types of EMG-sensor board arrangements in comparison with a benchmark configuration. The purpose is to evaluate the effect of the PCB metallization and identify the optimal antenna size. An overall 40 times40mathrmmmathrmm2\times 40\mathrm{m}\mathrm{m}^{2}times40mathrmmmathrmm2 device footprint is found to minimize the disturbing effects of the sensor circuit on the antenna performance and a read range up to 150 cm can be achieved.

Aeu-international Journal of Electronics and Communications, Jul 1, 2019

A low-cost energy-harvesting sensory headwear useful for tetraplegic people to drive home automat... more A low-cost energy-harvesting sensory headwear useful for tetraplegic people to drive home automation,

IEEE Journal of Biomedical and Health Informatics, 2020

Objective: The complex nature of Parkinson's disease (PD) makes difficult to rate its severity, m... more Objective: The complex nature of Parkinson's disease (PD) makes difficult to rate its severity, mainly based on visual inspection of motor impairments. Wearable sensors have been demonstrated to help overcoming such a difficulty, by providing objective measures of motor abnormalities. However, up to now those sensors have been used on advanced PD patients with evident motor impairment. As a novelty, here we report the impact of wearable sensors in the evaluation of motor abnormalities in newly diagnosed, untreated, namely de novo, patients. Methods: A network of wearable sensors was used to measure motor capabilities, in 30 de novo PD patients and 30 healthy subjects, while performing five motor tasks. Measurement data were used to determine motor features useful to highlight impairments and were compared with the corresponding clinical scores. Three classifiers were used to differentiate PD from healthy subjects. Results: Motor features gathered from wearable sensors showed a high degree of significance in discriminating the early untreated de novo PD patients from the healthy subjects, with 95% in accuracy. The rates of severity obtained from the measured features are partially in agreement with the clinical scores, with some highlighted, though justified, exceptions. Conclusion: Our findings support the feasibility of adopting wearable sensors in the detection of motor anomalies in early, untreated, PD patients. Significance: This work demonstrates that subtle motor impairments, occurring in de novo patients, can be evidenced by means of wearable sensors, providing clinicians with instrumental tools as suitable supports for early diagnosis, and subsequent management.

Springer eBooks, Jun 29, 2022

IEEE Transactions on Instrumentation and Measurement, 2021

We realized and tested a novel system aimed at discriminating different hand poses by means of an... more We realized and tested a novel system aimed at discriminating different hand poses by means of an active actuating and sensing approach realized by converting electromagnetic-to-mechanical waves (and vice-versa) and analyzing the characteristics of the waves after their travel through the bones and cartilage of the hand. The actuating part is realized through a transducer, placed on the dorsal part of the hand, performing electromagnetic to mechanical energy conversion. The sensing part is realized through an accelerometer, placed on a finger, performing mechanical to electromagnetic energy conversion. The way the sound propagates through the fingers mainly depend on the travelled path, on the angles of fingers flexion, and on the (un)matched conditions with surroundings. Therefore, the investigation of the characteristics of the returned signal (in phase shifts and power spectral densities) can furnish information for discriminating among different finger poses and different densities of touched materials. The system highly performed in repeatability and reproducibility of the measures, well discriminating among hand poses and among densities of touched materials.

Sensors, Dec 11, 2019

Currently, clinical evaluation represents the primary outcome measure in Parkinson's disease (PD)... more Currently, clinical evaluation represents the primary outcome measure in Parkinson's disease (PD). However, clinical evaluation may underscore some subtle motor impairments, hidden from the visual inspection of examiners. Technology-based objective measures are more frequently utilized to assess motor performance and objectively measure motor dysfunction. Gait and balance impairments, frequent complications in later disease stages, are poorly responsive to classic dopamine-replacement therapy. Although recent findings suggest that transcranial direct current stimulation (tDCS) can have a role in improving motor skills, there is scarce evidence for this, especially considering the difficulty to objectively assess motor function. Therefore, we used wearable electronics to measure motor abilities, and further evaluated the gait and balance features of 10 PD patients, before and (three days and one month) after the tDCS. To assess patients' abilities, we adopted six motor tasks, obtaining 72 meaningful motor features. According to the obtained results, wearable electronics demonstrated to be a valuable tool to measure the treatment response. Meanwhile the improvements from tDCS on gait and balance abilities of PD patients demonstrated to be generally partial and selective.

Applied sciences, Jul 25, 2023

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

IEEE Transactions on Instrumentation and Measurement, 2021

Sign languages (SLs) can aid in improving the communication between hearing impaired and hearing ... more Sign languages (SLs) can aid in improving the communication between hearing impaired and hearing communities, but only a limited number of hearing individuals understand it. SL recognition systems tackle this issue by using sensors to acquire gesture data later converted into spoken or written language by means of machine-learning algorithms. Within this frame, we propose a wearable electronic-based system for achieving automatic signer-independent recognition of Italian SL. The system is used for recognizing ten signs performed by 17 inexperienced signers. The wearable electronics measure hand, arm, and forearm gestures, by means of a sensory glove (equipped with ten flex sensors) and six inertial measurement units (IMUs). We adopt three classifiers: artificial neural network (ANN), kkk -nearest neighbors, and support vector machine, with ANN outperforming the others with an accuracy of 95.07%. However, the real key and novel aspect of this work concerns exploring the importance of each sensor for the overall classification accuracy, with the aim of determining the minimum number of sensors (and so minimizing the complexity of the wearable system) necessary to guarantee an acceptable accuracy. As a result, we could drop out three of the six IMUs, obtaining an accuracy as high as 93.91%. In addition, this valuable result was obtained using a signer-independent approach, which makes the application closer to a real-life situation.

Journal of the Neurological Sciences, Oct 1, 2021

Expert Systems With Applications, Jun 1, 2023

SN Computer Science , 2024

Current technologies allow acquiring whatever amount of data (even big data), from whatever syste... more Current technologies allow acquiring whatever amount of data (even big data), from whatever system (object, component, mechanism, network, implant, machinery, structure, asset, etc.), during whatever time lapse (secs, hours, weeks, years). Therefore, potentially it is possible to fully characterize any system for any time we need, with the possible consequence of creating a virtual copy, namely the digital twin (DT) of the system. When technology of DT meets an augmented reality scenario, the augmented digital twin (ADT) arises, when DT meets an artificial intelligence environment, the intelligent digital twin (IDT) arises. DTs, ADTs and IDTs are successfully adopted in electronics, mechanics, chemistry, manufacturing, science, sport, and more, but when adopted for the human body it comes out the human digital twin (HDT) or alternatively named virtual human simulator (VHS). When the VHS incorporates information from surroundings (other VHSs and environment), taking a cue from the particle-wave duality (the mix of matter and energy), we can name this super-VHS as the human digi-real duality (HDRD). This work is focused on defining the aforementioned acronyms, on evidencing their differences, advantages and successful case adoptions, but highlighting technology limits too, and on foreseeing new and intriguing possibilities.

Frontiers in Neurology, Jun 13, 2023

The analysis of vocal samples from patients with Parkinson's disease (PDP) can be relevant in sup... more The analysis of vocal samples from patients with Parkinson's disease (PDP) can be relevant in supporting early diagnosis and disease monitoring. Intriguingly, speech analysis embeds several complexities influenced by speaker characteristics (e.g., gender and language) and recording conditions (e.g., professional microphones or smartphones, supervised, or non-supervised data collection). Moreover, the set of vocal tasks performed, such as sustained phonation, reading text, or monologue, strongly a ects the speech dimension investigated, the feature extracted, and, as a consequence, the performance of the overall algorithm. Methods: We employed six datasets, including a cohort of Healthy Control (HC) participants and PDP from di erent nationalities (i.e., Italian, Spanish, Czech), recorded in variable scenarios through various devices (i.e., professional microphones and smartphones), and performing several speech exercises (i.e., vowel phonation, sentence repetition). Aiming to identify the e ectiveness of di erent vocal tasks and the trustworthiness of features independent of external co-factors such as language, gender, and data collection modality, we performed several intra-and inter-corpora statistical analyses. In addition, we compared the performance of di erent feature selection and classification models to evaluate the most robust and performing pipeline. Results: According to our results, the combined use of sustained phonation and sentence repetition should be preferred over a single exercise. As for the set of features, the Mel Frequency Cepstral Coe cients demonstrated to be among the most e ective parameters in discriminating between HC and PDP, also in the presence of heterogeneous languages and acquisition techniques. Conclusion: Even though preliminary, the results of this work can be exploited to define a speech protocol that can e ectively capture vocal alterations while minimizing the e ort required to the patient. Moreover, the statistical analysis identified a set of features minimally dependent on gender, language, and recording modalities. This discloses the feasibility of extensive cross-corpora tests to develop robust and reliable tools for disease monitoring and staging and PDP follow-up.

Springer eBooks, Jun 29, 2022

Hpb, Mar 1, 2019

stapler. Both, the right and left hepatic ducts were sutured side by side together to create a si... more stapler. Both, the right and left hepatic ducts were sutured side by side together to create a single bilioenteric anastomosis. Robotic hepaticojejunostomy was constructed with 2 running 3-0 V-Lock barbed sutures. A 10 Fr flat JP drain was placed dorsal to the hepaticojejunostomy. The patient tolerated the procedure well without intraoperative complications. Her postoperative recovery was uneventful. She was discharged home on postoperative day 4. Conclusion: The use of robotic technology in hepatobiliary operations is increasing but is still limited to a few specialized high-volume centers and in the hands of experts. Superior three-dimensional visualization and increased maneuverability with ease of suturing are only few of many advantages of the robotic technology.

Applied sciences, Apr 18, 2022

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

IEEE Journal of Biomedical and Health Informatics, Jul 1, 2022

OBJECTIVE In order to evaluate Parkinson disease patients response to therapeutic interventions, ... more OBJECTIVE In order to evaluate Parkinson disease patients response to therapeutic interventions, sources of information are mainly patient reports and clinicians assessment of motor functions. However, these sources can suffer from patients subjectivity and from inter/intra raters score variability. Our work aimed at determining the impact of wearable electronics and data analysis in objectifying the effectiveness of levodopa treatment. METHODS Seven motor tasks performed by thirty-six patients were measured by wearable electronics and related data were analyzed. This was at the time of therapy initiation (T0), and repeated after six (T1) and 12 months (T2). Wearable electronics consisted of inertial measurement units each equipped with 3-axis accelerometer and 3-axis gyroscope, while data analysis of ANOVA and Pearson correlation algorithms, in addition to a support vector machine (SVM) classification. RESULTS According to our findings, levodopa-based therapy alters the patients conditions in general, ameliorating something (e.g. bradykinesia), leaving unchanged others (e.g. tremor), but with poor correlation to the levodopa dose. CONCLUSION A technology-based approach can objectively assess levodopa-based therapy effectiveness. SIGNIFICANCE Novel devices can improve the accuracy of the assessment of motor function, by integrating the clinical evaluation and patient reports.

Springer eBooks, Jun 29, 2022

Bio-integrated wireless systems require to integrate electronic modules for bio-signal processing... more Bio-integrated wireless systems require to integrate electronic modules for bio-signal processing within a stretchable and soft skin-like device. The size and complexity of the PCB hosting circuitry cannot be separated from the design of the antenna used for the communication. Challenges arise when high frequencies are involved so that human body losses will deteriorate the radiation gain. This paper describes the design of a UHF-RFID epidermal antenna integrated with different types of EMG-sensor board arrangements in comparison with a benchmark configuration. The purpose is to evaluate the effect of the PCB metallization and identify the optimal antenna size. An overall 40 times40mathrmmmathrmm2\times 40\mathrm{m}\mathrm{m}^{2}times40mathrmmmathrmm2 device footprint is found to minimize the disturbing effects of the sensor circuit on the antenna performance and a read range up to 150 cm can be achieved.

Aeu-international Journal of Electronics and Communications, Jul 1, 2019

A low-cost energy-harvesting sensory headwear useful for tetraplegic people to drive home automat... more A low-cost energy-harvesting sensory headwear useful for tetraplegic people to drive home automation,

IEEE Journal of Biomedical and Health Informatics, 2020

Objective: The complex nature of Parkinson's disease (PD) makes difficult to rate its severity, m... more Objective: The complex nature of Parkinson's disease (PD) makes difficult to rate its severity, mainly based on visual inspection of motor impairments. Wearable sensors have been demonstrated to help overcoming such a difficulty, by providing objective measures of motor abnormalities. However, up to now those sensors have been used on advanced PD patients with evident motor impairment. As a novelty, here we report the impact of wearable sensors in the evaluation of motor abnormalities in newly diagnosed, untreated, namely de novo, patients. Methods: A network of wearable sensors was used to measure motor capabilities, in 30 de novo PD patients and 30 healthy subjects, while performing five motor tasks. Measurement data were used to determine motor features useful to highlight impairments and were compared with the corresponding clinical scores. Three classifiers were used to differentiate PD from healthy subjects. Results: Motor features gathered from wearable sensors showed a high degree of significance in discriminating the early untreated de novo PD patients from the healthy subjects, with 95% in accuracy. The rates of severity obtained from the measured features are partially in agreement with the clinical scores, with some highlighted, though justified, exceptions. Conclusion: Our findings support the feasibility of adopting wearable sensors in the detection of motor anomalies in early, untreated, PD patients. Significance: This work demonstrates that subtle motor impairments, occurring in de novo patients, can be evidenced by means of wearable sensors, providing clinicians with instrumental tools as suitable supports for early diagnosis, and subsequent management.

Springer eBooks, Jun 29, 2022

IEEE Transactions on Instrumentation and Measurement, 2021

We realized and tested a novel system aimed at discriminating different hand poses by means of an... more We realized and tested a novel system aimed at discriminating different hand poses by means of an active actuating and sensing approach realized by converting electromagnetic-to-mechanical waves (and vice-versa) and analyzing the characteristics of the waves after their travel through the bones and cartilage of the hand. The actuating part is realized through a transducer, placed on the dorsal part of the hand, performing electromagnetic to mechanical energy conversion. The sensing part is realized through an accelerometer, placed on a finger, performing mechanical to electromagnetic energy conversion. The way the sound propagates through the fingers mainly depend on the travelled path, on the angles of fingers flexion, and on the (un)matched conditions with surroundings. Therefore, the investigation of the characteristics of the returned signal (in phase shifts and power spectral densities) can furnish information for discriminating among different finger poses and different densities of touched materials. The system highly performed in repeatability and reproducibility of the measures, well discriminating among hand poses and among densities of touched materials.

Sensors, Dec 11, 2019

Currently, clinical evaluation represents the primary outcome measure in Parkinson's disease (PD)... more Currently, clinical evaluation represents the primary outcome measure in Parkinson's disease (PD). However, clinical evaluation may underscore some subtle motor impairments, hidden from the visual inspection of examiners. Technology-based objective measures are more frequently utilized to assess motor performance and objectively measure motor dysfunction. Gait and balance impairments, frequent complications in later disease stages, are poorly responsive to classic dopamine-replacement therapy. Although recent findings suggest that transcranial direct current stimulation (tDCS) can have a role in improving motor skills, there is scarce evidence for this, especially considering the difficulty to objectively assess motor function. Therefore, we used wearable electronics to measure motor abilities, and further evaluated the gait and balance features of 10 PD patients, before and (three days and one month) after the tDCS. To assess patients' abilities, we adopted six motor tasks, obtaining 72 meaningful motor features. According to the obtained results, wearable electronics demonstrated to be a valuable tool to measure the treatment response. Meanwhile the improvements from tDCS on gait and balance abilities of PD patients demonstrated to be generally partial and selective.

Applied sciences, Jul 25, 2023

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

IEEE Transactions on Instrumentation and Measurement, 2021

Sign languages (SLs) can aid in improving the communication between hearing impaired and hearing ... more Sign languages (SLs) can aid in improving the communication between hearing impaired and hearing communities, but only a limited number of hearing individuals understand it. SL recognition systems tackle this issue by using sensors to acquire gesture data later converted into spoken or written language by means of machine-learning algorithms. Within this frame, we propose a wearable electronic-based system for achieving automatic signer-independent recognition of Italian SL. The system is used for recognizing ten signs performed by 17 inexperienced signers. The wearable electronics measure hand, arm, and forearm gestures, by means of a sensory glove (equipped with ten flex sensors) and six inertial measurement units (IMUs). We adopt three classifiers: artificial neural network (ANN), kkk -nearest neighbors, and support vector machine, with ANN outperforming the others with an accuracy of 95.07%. However, the real key and novel aspect of this work concerns exploring the importance of each sensor for the overall classification accuracy, with the aim of determining the minimum number of sensors (and so minimizing the complexity of the wearable system) necessary to guarantee an acceptable accuracy. As a result, we could drop out three of the six IMUs, obtaining an accuracy as high as 93.91%. In addition, this valuable result was obtained using a signer-independent approach, which makes the application closer to a real-life situation.

Journal of the Neurological Sciences, Oct 1, 2021

Expert Systems With Applications, Jun 1, 2023