Recognition System of Human Fatigue State Based on Hip Gait Information in Gait Patterns
Round 1
Reviewer 1 Report
A well-written manuscript. I have a few suggestions that the authors might like to address:
1. Please refer to the following papers and try to follow these for the discussion sections. You may refer to this work if related:
10.1109/TSMCA.2012.2207111
10.1109/TSMCB.2012.2222374
2. Please elaborate on your experiments more in a technical way by adding the figures of the experimental setup and procedure.
Author Response
Response to Referees’ Comments(electronics-1960093)
We sincerely thank a lot for the precious comments on our manuscript (ID: electronics-1960093) given by the editor and reviewers, which greatly enabled us to express our views and improve our manuscript better. The revisions are highlighted in the revised manuscript.
Reviewers’ comments:
Reviewer #1: A well-written manuscript. I have a few suggestions that the authors might like to address:
Response:
We sincerely thank the reviewer’s positive comments on our work. We firmly believe that the reviewer's constructive suggestions will enhance our manuscript a lot, so that our manuscript can be better understood by future readers.
Point 1: Please refer to the following papers and try to follow these for the discussion sections. You may refer to this work if related:
10.1109/TSMCA.2012.2207111
10.1109/TSMCB.2012.2222374
Response 1:
We sincerely thank the reviewer for the careful and responsible attitudes. These articles truly inspires us a lot. We have added these references in the revised manuscript which have been highlighted on the Page 11.
Point 2: Please elaborate on your experiments more in a technical way by adding the figures of the experimental setup and procedure.
Response 2:
We are grateful for the reviewer’s detailed comments. The figures of the experimental setup and procedure from recognition system of human fatigue state is shown in the Figure R1 to Figure R3 and has been added to the manuscript on Page 4 to Page 5 as Figure 2 to Figure 4. The detailed explanation is as follows and has been added to the manuscript on Page 4 to Page 5.
Figure R1. (a) Wearable hip gait collection device; (b) Circuit design of the collection system.
Figure R2. (a) The overall wearing effect of the collection device; (b) Subjects' gait information collection process.
The hip and knee joints of humans are used in this study to gather data on lower limb joint angles utilizing angle sensors. The data gathered by all four joints is transferred to the host computer via a module inside the left hip joint, where the control circuit of the collection system is housed. The left hip joint collection device is shown in Figure R1(a). The device's angle sensor features a pivot shaft attached to the thigh linkage to track the movement of the thigh. The hardware in this device is in the LQP48 package, which has excellent computational performance and low power consumption, and employs STM32F103C8T6 as the main control chip. To finish the data transfer from the lower computer to the upper computer, this experiment is connected to the Bluetooth communi-cation module via the serial port. The board must be built with a 35 mm radius circular for simple installation in the housing, with the hollow part serving as the mounting place for the angle sensor (as illustrated in Figure R1(b)). The angle sensor with a measurement range of 0-333 degrees is chosen to be put on the rotor of the wearable device in order to gather the angle data of the hip and knee joints in the range of 0-90 degrees rotation during the walking process. The device's measured operating voltage, current, and total power con-sumption are all 3.6 V, 6.7 mA, and 24.12 mW, respectively. A lithium battery with a 3.7 V and 500 mA standard serves as the built-in power source. Figure R2(a) depicts the wearable collection device's actual operation, showing how well it fits the human torso, thigh, and calf torso to enable accurate data collection from the angle sensor. The device's bottom portion is fastened to the thigh with a bandage, while the upper portion is secured to the human torso using a belt. During the walking process, the lower arm movement will be consistent with the thigh movement to achieve accurate measurement of hip joint angle information. The other component is the knee joint collection device, which measures the knee joint angle by having its top part fixed to the thigh and its lower part fixed to the calf. Figure R2(b) depicts the procedure for gathering information about the subject's gait.
Figure R3. Block diagram of collection system design.
Figure R3 depicts the gait information collection system's overall design block diagram. There are hardware and software components to the system. In the previous paragraph, the hardware component of the gait information collection system was thoroughly ex-plained. This component is primarily in charge of data analog-to-digital conversion, data collection, data encapsulation into frames, and data sending and receiving. The gait in-formation collection system's software component was created using the Python programming language, and its features include data processing, data display, and data storage.
Please see the attachment.
Author Response File: 
Author Response.docx
Reviewer 2 Report
The authors presented a wearable system for monitoring hip dynamics during human walking and a machine learning method for evaluating the fatigue level of the subjects. Though the work is interesting and has the potential to be useful for the researchers and designers working in the field of rehabilitation robotics. The experimental evaluation by the authors is really appreciable, but the reviewer wants to suggest a detailed analysis should be included with respect to the theoretical point of view of the work. Although, the manuscript can be accepted for publication as a short paper in its present form.
Author Response
Response to Referees’ Comments(electronics-1960093)
We sincerely thank a lot for the precious comments on our manuscript (ID: electronics-1960093) given by the editor and reviewers, which greatly enabled us to express our views and improve our manuscript better. The revisions are highlighted in the revised manuscript.
Reviewers’ comments:
Reviewer #2: The authors presented a wearable system for monitoring hip dynamics during human walking and a machine learning method for evaluating the fatigue level of the subjects. Though the work is interesting and has the potential to be useful for the researchers and designers working in the field of rehabilitation robotics. The experimental evaluation by the authors is really appreciable, but the reviewer wants to suggest a detailed analysis should be included with respect to the theoretical point of view of the work. Although, the manuscript can be accepted for publication as a short paper in its present form.
Response:
We are extremely grateful for the reviewer’s affirmation of our work as “the work is interesting and has the potential to be useful for the researchers and designers working in the field of rehabilitation robotics. We are grateful for the reviewer’s detailed comments. The figures of the experimental setup and procedure from recognition system of human fatigue state is shown in the Figure R1 to Figure R3 and has been added to the manuscript on Page 4 to Page 5 as Figure 2 to Figure 4. The detailed explanation is as follows and has been added to the manuscript on Page 4 to Page 5.
Figure R1. (a) Wearable hip gait collection device; (b) Circuit design of the collection system.
Figure R2. (a) The overall wearing effect of the collection device; (b) Subjects' gait information collection process.
The hip and knee joints of humans are used in this study to gather data on lower limb joint angles utilizing angle sensors. The data gathered by all four joints is transferred to the host computer via a module inside the left hip joint, where the control circuit of the collection system is housed. The left hip joint collection device is shown in Figure R1(a). The device's angle sensor features a pivot shaft attached to the thigh linkage to track the movement of the thigh. The hardware in this device is in the LQP48 package, which has excellent computational performance and low power consumption, and employs STM32F103C8T6 as the main control chip. To finish the data transfer from the lower computer to the upper computer, this experiment is connected to the Bluetooth communication module via the serial port. The board must be built with a 35 mm radius circular for simple installation in the housing, with the hollow part serving as the mounting place for the angle sensor (as illustrated in Figure R1(b)). The angle sensor with a measurement range of 0-333 degrees is chosen to be put on the rotor of the wearable device in order to gather the angle data of the hip and knee joints in the range of 0-90 degrees rotation during the walking process. The device's measured operating voltage, current, and total power con-sumption are all 3.6 V, 6.7 mA, and 24.12 mW, respectively. A lithium battery with a 3.7 V and 500 mA standard serves as the built-in power source. Figure R2(a) depicts the wearable collection device's actual operation, showing how well it fits the human torso, thigh, and calf torso to enable accurate data collection from the angle sensor. The device's bottom portion is fastened to the thigh with a bandage, while the upper portion is secured to the human torso using a belt. During the walking process, the lower arm movement will be consistent with the thigh movement to achieve accurate measurement of hip joint angle information. The other component is the knee joint collection device, which measures the knee joint angle by having its top part fixed to the thigh and its lower part fixed to the calf. Figure R2(b) depicts the procedure for gathering information about the subject's gait.
Figure R3. Block diagram of collection system design.
Figure R3 depicts the gait information collection system's overall design block diagram. There are hardware and software components to the system. In the previous paragraph, the hardware component of the gait information collection system was thoroughly ex-plained. This component is primarily in charge of data analog-to-digital conversion, data collection, data encapsulation into frames, and data sending and receiving. The gait information collection system's software component was created using the Python programming language, and its features include data processing, data display, and data storage.
Please see the attachment.
Author Response File: 
Author Response.pdf
Round 2
Reviewer 2 Report
Though the authors have improved the manuscript by including the section "Gait information collection device"; but there is a need of further improvement in the manuscript before it can be acceptable for publication.
