Inconsistent steps data

Data & Analysis
1

Hi there,

I went into an error while extracting the steps data.
Usually it collects the value, source, type and unit. However, in one record it collects distance, floors_descended, event, active_pace, floors_ascended, value, pace and cadence. I wonder why there is an inconsistency in collecting the steps data? What operation creates/activate such record? Thank you!

2

Hello,

Can you share a copy of the record (de-identified, without participant information or ID) that is collecting all those data types?

For iPhone users, those data types (floors_descended, distance, average_active_pace, etc.) are typically collected automatically by the lamp.steps sensor, but they should be stored as values for the ‘type’ key in the ‘data’ dictionary. If in this case, these values are not being stored that way, this may be a bug as the schema should be the same across all devices.

Thanks!

3

Hi Lucy,

Here is a copy of one ID I extracted.

------- {‘value’: 68, ‘source’: None, ‘type’: ‘step_count’, ‘unit’: ‘count’}

------- {‘value’: 0, ‘source’: None, ‘type’: ‘floors_descended’, ‘unit’: ‘count’}

------- {‘value’: 0, ‘source’: None, ‘type’: ‘floors_ascended’, ‘unit’: ‘count’}

------- {‘value’: 2.1533664294886, ‘source’: None, ‘type’: ‘average_active_pace’, ‘unit’: ‘seconds per meter’}

------- {‘value’: 46.140000000130385, ‘source’: None, ‘type’: ‘distance’, ‘unit’: ‘meter’}

------- {‘value’: 68, ‘source’: None, ‘type’: ‘step_count’, ‘unit’: ‘count’}

------- {‘value’: 0, ‘source’: None, ‘type’: ‘floors_descended’, ‘unit’: ‘count’}

------- {‘value’: 0, ‘source’: None, ‘type’: ‘floors_ascended’, ‘unit’: ‘count’}

------- {‘value’: 2.1533664294886, ‘source’: None, ‘type’: ‘average_active_pace’, ‘unit’: ‘seconds per meter’}

------- {‘value’: 46.140000000130385, ‘source’: None, ‘type’: ‘distance’, ‘unit’: ‘meter’}

------- {‘value’: 68, ‘source’: None, ‘type’: ‘step_count’, ‘unit’: ‘count’}

------- {‘distance’: 7612.655867523979, ‘floors_descended’: 10, ‘event’: ‘pause’, ‘active_pace’: 0.8589977033044179, ‘floors_ascended’: 10, ‘value’: 11168, ‘pace’: 0, ‘cadence’: 0}

It seems they are not stored in the ‘type’. Does it look like a bug to you? Thanks.

4

Thanks for this – would you mind sending the whole output of the raw data for this participant, so including things like ‘sensor’ and ‘timestamp’?

5

No problem. Here is a whole output for the most recent data points:

18789 ------- {‘sensor’: ‘lamp.steps’, ‘data’: {‘value’: 2.1533664294886, ‘source’: None, ‘type’: ‘average_active_pace’, ‘unit’: ‘seconds per meter’}, ‘timestamp’: 1650801027324}
18790 ------- {‘sensor’: ‘lamp.steps’, ‘data’: {‘value’: 46.140000000130385, ‘source’: None, ‘type’: ‘distance’, ‘unit’: ‘meter’}, ‘timestamp’: 1650801027324}
18791 ------- {‘sensor’: ‘lamp.steps’, ‘data’: {‘value’: 68, ‘source’: None, ‘type’: ‘step_count’, ‘unit’: ‘count’}, ‘timestamp’: 1650801027324}
18792 ------- {‘sensor’: ‘lamp.steps’, ‘data’: {‘value’: 0, ‘source’: None, ‘type’: ‘floors_descended’, ‘unit’: ‘count’}, ‘timestamp’: 1650801024465}
18793 ------- {‘sensor’: ‘lamp.steps’, ‘data’: {‘value’: 0, ‘source’: None, ‘type’: ‘floors_ascended’, ‘unit’: ‘count’}, ‘timestamp’: 1650801024465}
18794 ------- {‘sensor’: ‘lamp.steps’, ‘data’: {‘value’: 2.1533664294886, ‘source’: None, ‘type’: ‘average_active_pace’, ‘unit’: ‘seconds per meter’}, ‘timestamp’: 1650801024465}
18795 ------- {‘sensor’: ‘lamp.steps’, ‘data’: {‘value’: 46.140000000130385, ‘source’: None, ‘type’: ‘distance’, ‘unit’: ‘meter’}, ‘timestamp’: 1650801024465}
18796 ------- {‘sensor’: ‘lamp.steps’, ‘data’: {‘value’: 68, ‘source’: None, ‘type’: ‘step_count’, ‘unit’: ‘count’}, ‘timestamp’: 1650801024465}
18797 ------- {‘sensor’: ‘lamp.steps’, ‘data’: {‘distance’: 7612.655867523979, ‘floors_descended’: 10, ‘event’: ‘pause’, ‘active_pace’: 0.8589977033044179, ‘floors_ascended’: 10, ‘value’: 11168, ‘pace’: 0, ‘cadence’: 0}, ‘timestamp’: 1650675351455}

6

This does look like a bug – thank you for bringing it to our attention! We will work on a fix and keep you updated.

7

Thank you!

8

Hi again,

We just looked into it, and this bug was actually caught earlier this year and was resolved in May. Since the data you’re looking at is from before it was resolved, that is why the issue is popping up, but it shouldn’t impact any data from after May of 2022. I hope this helps!

9

Hi Lucy,

I see. Thank you for looking into this issue and such a quick reply. I am happy that the problem was resolved in May. For the data collected earlier than May 2022, I will delete the outliers after download from mindlamp. Thanks again!