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Hongzhe’s Status Report for 09/23/2023

For this week, we had a major change in the project plan, and here is the work I did. 

For the past project regarding patient monitoring. I interviewed some doctors and nurses for background information to prove the usability of the project. The interview consists of gathering symptoms, especially behavioral symptoms, such as chest pain, vomit, increasing breath, seizure, etc. At the same time, the interview focusing on nursing assistants is more about the medical care system in hospitals and nursing homes, attempting to prove that the usual alarm system is not quick enough given the multiple layers of notification all the way to doctors. Please note that the interviews are conducted with Chinese medical system workers instead of in the US, and there might be discrepancy on how US hospitals work.

Then after having abundant communications with the course staff, we decided to change the project to a Taiji instruction application based on OpenPose given that this idea is more solid with more accessible online resources and static gesture references.

Indeed, my team and I are slightly behind schedule since we switched the project, but we will keep up for the future weeks by accelerating the schedule. At the same time, since the Taiji context has more gesture resources online, we could skip the raw data collection process before, giving us more time to work on the technical portion.

I am hoping to be able to successfully run OpenPose on my own machine for the next week so that we can start to use OpenPose for processing some Taiji gestures.

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Team Status Report for 09/23/2023

Our team experienced drastic changes this week as we changed our project theme completely from hospital setting in to the traditional Chinese Taiji posture detection and instructor. After the discussion with course staff in the past few days, we recognized some usability and cost issues not apparent to us initially. Such discrepancies cost us substantial time and effort to justify our work. Thus, by the end of the week, we decided to switch gears and move on to the current topic–Taiji Pose Recognition Project: Taichine.

We adopted the idea of Taiji instructor since it is not a major change from our original idea. Most hardware and software usage will stay the same, but the overall setting of Taiji is much more manageable regarding a semester-long project. We still plan to use the camera-RasPi-backend setup as before, but the hardware will have enough capabilities to detect, classify, and evaluate body posture in real-time since Taiji pose recognition has higher tolerance in recognition efficiency. There will also be more online resources available to us while fewer privacy concerns should arise. We will spend less time monitoring personal data and focus on certain actions/routines so that we can offer clear evaluations in short periods of time.

It has been a week of transitions and chaos, but we successfully identified valuable online resources on Taiji postures and its recognition, which we could apply as training sets into our OpenPose algorithm. For the next week, we will focus on fixiating our hardware/software quantifications and formulate an optimal design for our system. If time allows, we plan to start data collection for our machine learning process. We will make necessary changes to our schedule and make sure we do not fall behind in the upcoming weeks, when working on Design review and training our models.

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Shiheng’s Status Report for 09/23/2023

After an intense discussion with Professor Tamal during the Friday meeting, we discovered the justification for our initial plan in terms of costs and applicability was not strong and viable. Understanding the difficulties and hardships we are going to meet using Openpose in patient behavior detection, I contributed to the change of topic into Taiji instructor. With reference to yoga instructor available online, we decided to follow a similar trend but carry out it differently since Taiji is more concentrated on the flow of body motion instead of static data points. We could control the cost easily through justification provided to monitor larger motions of Taiji using Openpose and the setup of one camera to provide back real time justification and evaluation of the body posture, instead of the original plan on patients, which we ignored the class of patients which are bedridden and would have continuous minor movements instead of large motions which normal people would behave.

Gathering data and formulating them are the main progress I made in the past few days after the project change, using Ray’s reference body positions, I identified some body positions that are concise for beginners to learn and could possibly be identified through the Openpose algorithm. I reckon these positions will be clearly identified in low-cost cameras and meet the requirements of the Raspberry Pi we tend to use in the project.

Though we are behind on scheduling, we have advanced greatly in the data collection and classification part which hindered us greatly on the previous project. I believe we could catch up in the following weeks and advance greatly into our project.

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Ray’s Status Report for 09/23/2023

This week, I presented our team’s original idea “Patient Monitor System” to the class. After the presentation, my teammates and I received feedback from instructors and, upon reconsideration, we decide to switch to the more applicable idea of designing a Taiji Training monitor system. To build upon this new idea, I searched for relevant papers and researches on pose recognition. In particular, I found and skimmed through the paper “3D Human Pose Estimation on Taiji Sequence” [1], finding it very relevant to our new project idea while targeting a different goal. In particular, the part where the conversion from 2D joints to 3D joints using neural network is intriguing and worth looking into.

My progress, along with our team’s schedule, is a bit behind due to our change in plan. To catch up on our original schedule, we will rework on our abstract to establish a reliable ground for our new idea for the first few days in the next week, and try to get the tasks originally planned for next week finished after we have a clear plan for the system we want to design.

In particular, I want to lay out how our systems will recognize and evaluate Taiji Poses. The Taiji Poses we plan to work with is the 24-form-Taiji sequence, there are clear ground-truth poses in this sequence for machine learning. We also have the idea of letting our user input the Taiji videos of their choices. We would also want to find a good way for the users to know how good their Taiji Poses are; some possible solutions to this might be an LED screen or a programmable LED unit. I also hope to make plenty of progress in our data collection next week, since data collection for our current idea is considerably simpler than for our previous idea.

[1]https://etda.libraries.psu.edu/files/final_submissions/17625