A Real-Time, Open-Source, IoT-like, Wearable Monitoring Platform
Round 1
Reviewer 1 Report
The authors developed an IoT-like modular and fully open-source platform composed of two main blocks that connect multiple devices (the sensor fusion unit) and is monitoring real-time process as well as store the sensors’ data through the internet (the remote storing and processing ). The patform was tested on 15 subjects and the results The features computed from each participant’s signal by the WMP during the experimental timeline were statistically analyzed to evaluate whether the platform was reliable in recording significant variations of the nervous system activity during the stressor task.
The results are demonstrating the possibility of connecting a wide range of ad-hoc heterogeneous sensors into a platform that could be used in many application contexts, however, a fine tunning for each aptient is required in order to perform a continuous health monitoring taking into consideration variations generated by temporal dynamics or emotional phenomena.
The article is well structured and written, the results clearly presented. I would reccomend to be published as it is.
Author Response
We are grateful to the reviewer for showing appreciation for our work.
Reviewer 2 Report
The manuscript entitled "A real-time, open-source, IoT-like, wearable monitoring platform “is a good work on the Computer Science.
Author Response
We are grateful to the reviewer for showing appreciation for our work
Reviewer 3 Report
Baldini et al. have developed a modular and fully open-source wearable monitoring platform integrating multiple commercially available devices to process physiological data in a real-time fashion. The platform is integrated into an IoT-like distributed architecture composed of two main blocks: the sensor fusion unit and the remote data storage and processing block. I recommend acceptance of the manuscript after minor revision.
1. The novelty of this work has not been clearly presented since the devices are commercially available.
2. The number and words in Figures 6 and 7 are too small.
3. The format of the References is inconsistent.
Author Response
Reviewer's Comment: Baldini et al. have developed a modular and fully open-source wearable monitoring platform integrating multiple commercially available devices to process physiological data in a real-time fashion. The platform is integrated into an IoT-like distributed architecture composed of two main blocks: the sensor fusion unit and the remote data storage and processing block. I recommend acceptance of the manuscript after minor revision.
Author's reply: We are grateful to the reviewer for showing appreciation for our work. We did our best to carefully address all issues. Please see the details below.
Reviewer's Comment: 1. The novelty of this work has not been clearly presented since the devices are commercially available.
Author's reply: Thank you for this comment. The reviewer is right, in fact, the devices connected to our platform are commercial devices. The novelty is not in the devices used as an exemplary application in our study, however, it is in the possibility of connecting multiple devices (commercial or not) to the platform maintaining high computational performance and using open-source components. In other words, the system shows high scalability and computational performance integrated into an IoT-like architecture for real-time processing applications. These characteristics are difficult to find in a single solution, nevertheless, this is not the only novelty of the study. Indeed, our study combines for the first time, all these characteristics in an open-source system that is comprised of third-parties open components continuously maintained by a large community. This means that, on the one hand, the risk of becoming obsolete is very low, on the other, the solution is always updated and secure. This information is included in the revised version of the manuscript.
Reviewer's Comment: 2. The number and words in Figures 6 and 7 are too small.
Author's reply: Thank you for this comment. In the revised version of the manuscript we have improved the readability of figures 6 and 7,
Reviewer's Comment: 3. The format of the References is inconsistent.
Author's reply: Thank you for this comment. The format of the reference is now fixed.
Reviewer 4 Report
The present paper proposes an architecture for an infra-structure to collect, store, and process data gathered from multiple wearable physiological signs sensing devices.
This is a highly relevant topic given the need to promote the advantages brought by wearable devices in terms of the more flexible and facilitated access to fitness and health monitoring. Thus the topic is in fact not knew and different efforts have been made to achieve such goal. In fact, one can mention, e. g., the Activeos (https://activeos.com), Personal Health Dashboard Bahmani, A., Alavi, A., Buergel, T. et al. A scalable, secure, and interoperable platform for deep data-driven health management. Nat Commun 12, 5757 (2021). https://doi.org/10.1038/s41467-021-26040-1) , the RADAR-base mHealth platform - Leverage wearable sensor data , and OpenHealth: Open Source Platform for Wearable Health Monitoring (https://arxiv.org/abs/1903.03168).
None of these initiatives/proposals is addressed in this paper. The authors should include, in the state of the art, a revision of previous developments and compare their WMP proposal with these, focusing on the distinctive features.
The paper is well written and organized, but:
- A more detailed description of the platform architecture should be included in order to let the reader know what are the real issues involved in the communications and interfacing of the various devices;
- Include a Conclusions section
- Correct some typos , such as : “intervention [REF ALBE]”, “the remote data storage and processing block (RDSPU)”, “EEG system has been choosenchosen”
- In “We recruited 15 healthy subjects (8 female, age= 28±4) to test” it is not clear whether the male subjects are also 28±4 years old.
- The S.T.A.I Y1 scores should be introduced for a better reading
Author Response
Reviewer's comment: The present paper proposes an architecture for an infra-structure to collect, store, and process data gathered from multiple wearable physiological signs sensing devices.
This is a highly relevant topic given the need to promote the advantages brought by wearable devices in terms of the more flexible and facilitated access to fitness and health monitoring. Thus the topic is in fact not knew and different efforts have been made to achieve such goal. In fact, one can mention, e. g., the Activeos (https://activeos.com), Personal Health Dashboard Bahmani, A., Alavi, A., Buergel, T. et al. A scalable, secure, and interoperable platform for deep data-driven health management. Nat Commun 12, 5757 (2021). https://doi.org/10.1038/s41467-021-26040-1) , the RADAR-base mHealth platform - Leverage wearable sensor data , and OpenHealth: Open Source Platform for Wearable Health Monitoring (https://arxiv.org/abs/1903.03168).
None of these initiatives/proposals is addressed in this paper. The authors should include, in the state of the art, a revision of previous developments and compare their WMP proposal with these, focusing on the distinctive features.
Answer’s reply: We are grateful to the reviewer for considering our work. In the revised version of the manuscript, we have now enriched the introduction section including a description of the aforementioned previous studies and the novelties introduced by our proposed platform.
Reviewer's comment: The paper is well written and organized, but:
- A more detailed description of the platform architecture should be included in order to let the reader know what are the real issues involved in the communications and interfacing of the various devices;
Answer’s reply: Thank you for your comment. We have now added a more detailed description of the sensor fusion unit including the issues involved in the communications and interfacing of the various devices and our solutions.
Reviewer's comment: Include a Conclusions section
Answer’s reply: A Conclusion section has now been added to the revised version of the manuscript.
Reviewer's comment: Correct some typos , such as : “intervention [REF ALBE]”, “the remote data storage and processing block (RDSPU)”, “EEG system has been choosenchosen”
Answer’s reply: Thank you for your comment, In the revised version of the manuscript, we have fixed all typos and added the missing ref: Nabian, M., Yin, Y., Wormwood, J., Quigley, K. S., Barrett, L. F., & Ostadabbas, S. (2018). An open-source feature extraction tool for the analysis of peripheral physiological data. IEEE journal of translational engineering in health and medicine, 6, 1-11.
Reviewer's comment: In “We recruited 15 healthy subjects (8 female, age= 28±4) to test” it is not clear whether the male subjects are also 28±4 years old.
Answer’s reply: The age reported in the manuscript referred to both males and females. We have now clarified this point by specifying that this is the average and standard deviation among all subjects.
Reviewer's comment: The S.T.A.I Y1 scores should be introduced for a better reading
Answer’s reply: Thank you for this comment, we have now included a paragraph to better introduce the S.T.A.I Y1 questionnaire.
