未越狱设备提取数据

Health data is collected every time you have your phone in your pocket. Apple or Android, the phones are equipped with a pedometer that counts your steps. Hence, health data is recorded. This data could be your one free data mart for a simple Machine Learning or some other project related to Health data. It’s yours and free to use!. Let’s see how we can export data from the Samsung S-Health App.

每当您将手机放在口袋中时，都会收集健康数据。 在Apple或Android上，手机配有计步器，可以计算您的步数。 因此，记录健康数据。 该数据可以是简单机器学习或其他与健康数据相关的项目的免费数据集市。 它是您的，免费使用！ 让我们看看如何从Samsung S-Health App导出数据。

The data download feature is available in your Samsung health app.

三星健康应用程序中提供了数据下载功能。

This probably is the easiest thing to do. However, understanding the data is a bit complicated. Let’s go through each of the file and its content to understand how Samsung health app stores data.

这可能是最容易的事情。 但是，了解数据有点复杂。 让我们浏览每个文件及其内容，以了解Samsung Health App如何存储数据。

You will see the following set of files with data. In place of T you’ll see the export timestamp. In the files folder, you’ll see the profile picture image. In the folder named jsons, you can find the JSON objects for data referred in the CSV files (I’ll not talk about JSONS in this article). Please note that the data columns of CSV files will also contain the package extension com.samsung.health. However, for the simplicity of the text, I will ignore when I explain the content of the CSV files.

您将看到以下带有数据的文件集。 代替T您将看到导出时间戳。 在文件文件夹中，您将看到个人资料图片图像。 在名为jsons的文件夹中，您可以找到CSV文件中引用的数据的JSON对象(本文中不再讨论JSONS)。 请注意，CSV文件的数据列还将包含软件包扩展名com.samsung.health 。 但是，为了文字简洁起见，当我解释CSV文件的内容时，我将忽略它。

Photo by Emiliano Cicero on Unsplash Emiliano Cicero在 Unsplash上的 照片

These are the files that contain data from the sensors including heart rate data and steps from the Galaxy Watch and the Phone itself. Step counts are collected from pedometer and accelerometer sensors. Heart rate is measured through the PPG (Photoplethysmogram) sensor in your watch. For these data, you have to look into the following files.

这些文件包含来自传感器的数据，包括心率数据以及Galaxy Watch和Phone本身的步骤。 步数是从计步器和加速度计传感器收集的。 心率通过手表中的PPG(光电容积描记)传感器测量。 对于这些数据，您必须查看以下文件。

Heart rate data are included in the following file.

心率数据包含在以下文件中。

The important information in this file is the update_time and heart_rate columns. You will also find the min and max values along with end_time, which shows the end of the recording.

该文件中的重要信息是update_time和heart_rate列。 您还将找到最小和最大值以及显示记录结束的end_time 。

Heart Rate Information

心率信息

Out of curiosity, I plotted a histogram of my heart rates to see how my heart behaves. It seems I have a heart rate in the range 65–80bps. Googling resulted in “A normal resting heart rate for adults ranges from 60 to 100 beats per minute”. I guess the histogram makes sense. One of the main concerns, when I bought the watch, was to keep a note of my heart rate. Because, usually at the doctors, I have an above-average heart rate with a panicked person’s blood pressure. Read here if you want to know more about that scenario at Doctors.

出于好奇，我绘制了心率的直方图，以查看我的心脏的行为。 看来我的心律在65-80bp s范围内。 谷歌搜索导致“成年人的正常静息心率范围为每分钟60到100次跳动” 。 我猜直方图是有道理的。 当我购买手表时，主要要考虑的问题之一是记下我的心律。 因为通常在医生那里，我的心跳速度高于平均水平，而患者的血压却感到恐慌。 如果您想在Doctors上了解有关该场景的更多信息，请阅读此处 。

Hear Rata Histogram

听到Rata直方图

Photo by Chander R on Unsplash Chander R在 Unsplash上的 照片

Step tracker data are available in the following files;

以下文件中提供了步骤跟踪器数据；

Daily Summary 每日总结

In the step_daily_trend you will see the daily values with step count, calories burnt, distance walked and the speed. However, in the pedometer_step_count you will find all the step information including running steps, walking steps. Basically this file contains the pedometer tracking information. In the last file (pedometer_day_summary), you can find the daily step summaries. Which might be enough for most of the tasks.

在step_daily_trend中，您将看到每日数值，包括步数，燃烧的卡路里，行走的距离和速度。 但是，在pedometer_step_count中，您将找到所有步骤信息，包括跑步步骤，步行步骤。 基本上，此文件包含计步器跟踪信息。 在最后一个文件( pedometer_day_summary )中，您可以找到每日步骤摘要。 对于大多数任务而言，这可能就足够了。

Let’s try to do some simple analysis of these data.

让我们尝试对这些数据进行一些简单的分析。

Step Counts vs Date 步数与日期

The above observation sort of aligns with the seasonal changes here in Australia. During the time June to December, we have cold temperatures. From December to June, we have much better running weather. However, COVID-19 came into play here in Canberra during the April and May, hence the low activity. However, in June my wife and I walked and tried to get back on the shape so we can eat out a lot during our anniversary period.

上述观察结果与澳大利亚这里的季节性变化相吻合。 在6月至12月的这段时间里，气温较低。 从12月到6月，我们的跑步天气要好得多。 但是，COVID-19在4月和5月在堪培拉开始活动，因此活动量很低。 但是，在六月，我和妻子走过路，试图恢复身材，这样一来周年纪念期间我们可以吃很多东西。

Step count isn’t quite a generic measure of activity. One might workout in a gym without any step count yet burning a lot of fat. Such activities are usually measured by calories using the heart rate sensor. However, as you can see below, my calorie counts are somewhat correlated with the step counts (There is a slight deviation of the X-axis, but they are close). This is because the only workout I prefer is running or jogging.

步数并不是一般的活动量度。 一个人可以在健身房锻炼而无需花费很多时间，却消耗了大量脂肪。 通常使用心率传感器通过卡路里来测量此类活动。 但是，正如您在下面看到的那样，我的卡路里数与步数有一定的相关性(X轴略有偏差，但是很接近)。 这是因为我更喜欢的唯一锻炼是跑步或慢跑。

Calories Burnt vs Date 卡路里消耗与日期

Something interesting is visible. On days I have run, I haven’t made many steps. In contrast, on walking days I have made it over 10000 steps. I wonder, whether I get tired on days I walk or the running steps aren’t counted for daily step count. Something I shall investigate in another article though.

有趣的东西是可见的。 在跑步的日子里，我并没有采取很多步骤。 相反，在步行的日子里，我走了10000多步。 我想知道，无论是在走路的日子里是否累了，还是每天的跑步步数都不算在内。 不过，我将在另一篇文章中对此进行调查。

There is more information including, weight and carb intakes. For that, you’ll have to have them recorded manually. However, there are some insightful data in the following file.

有更多信息，包括体重和碳水化合物摄入量。 为此，您必须手动记录它们。 但是，以下文件中有一些有见地的数据。

Exercise Weather Data 运动天气数据

However, in order to use this file, you’ll have to combine this with the exercise file. That is for another article!

但是，为了使用此文件，您必须将其与练习文件结合在一起。 那是另一篇文章！

I hope this article would make a useful outcome of the data that you most often get rid of. Happy reading!

我希望本文能为您最常用的数据带来有益的结果。 祝您阅读愉快！