crosstyan/hr_visualize
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

feat: Refactor HR data processing and visualization with new HrPacket model

Browse Source
This commit is contained in:
crosstyan
2025-02-24 16:27:22 +08:00
parent 6407307976
commit 6a6622eff0
3 changed files with 87 additions and 50 deletions
Download Patch File Download Diff File Expand all files Collapse all files

73
app/model/__init__.py
View File

@ -138,3 +138,76 @@ class AlgoReport(BaseModel):
accel_z=accel_z,
data=data,
)
class HrConfidence(IntEnum):
"""Equivalent to max::HR_CONFIDENCE"""
ZERO = 0
LOW = 1
MEDIUM = 2
HIGH = 3
def hr_confidence_to_num(hr_confidence: HrConfidence) -> float:
if hr_confidence == HrConfidence.ZERO:
return 0
elif hr_confidence == HrConfidence.LOW:
return 25
elif hr_confidence == HrConfidence.MEDIUM:
return 62.5
elif hr_confidence == HrConfidence.HIGH:
return 100
else:
raise ValueError(f"Invalid HR confidence: {hr_confidence}")
@dataclass
class HrStatusFlags:
# 2 bits
hr_confidence: HrConfidence
# 1 bit
is_active: bool
# 1 bit
is_on_skin: bool
# 4 bits
battery_level: int
@staticmethod
def unmarshal(data: bytes) -> "HrStatusFlags":
val = data[0]
return HrStatusFlags(
hr_confidence=HrConfidence(val & 0b11),
is_active=(val & 0b100) != 0,
is_on_skin=(val & 0b1000) != 0,
battery_level=val >> 4,
)
@dataclass
class HrPacket:
# 8 bits
status: HrStatusFlags
# 8 bits
id: int
# 8 bits
hr: int
# 8 bits (as `n`) + n x 24 bits
raw_data: list[int]
@staticmethod
def unmarshal(data: bytes) -> "HrPacket":
status = HrStatusFlags.unmarshal(data[0:1])
id = data[1]
hr = data[2]
raw_data_count = data[3]
raw_data_payload = data[4:]
if len(raw_data_payload) != (expected_raw_data_len := raw_data_count * 3):
raise ValueError(
f"Invalid raw data payload length: {len(raw_data_payload)}, expected {expected_raw_data_len}"
)
raw_data = [
int.from_bytes(raw_data_payload[i : i + 3], "little")
for i in range(0, expected_raw_data_len, 3)
]
return HrPacket(status, id, hr, raw_data)

4
ble_forward.py
View File

@ -6,11 +6,11 @@ from typing import Final, Optional
from loguru import logger
from anyio import create_udp_socket, create_connected_udp_socket
DEVICE_NAME: Final[str] = "MAX-BAND"
DEVICE_NAME: Final[str] = "MAX-HUB"
UDP_SERVER_HOST: Final[str] = "localhost"
UDP_SERVER_PORT: Final[int] = 50_000
BLE_HR_SERVICE_UUID: Final[str] = "180D"
BLE_HR_CHARACTERISTIC_RAW_UUID: Final[str] = "c4f5233d-430a-4ca1-bb60-1d896c10e807"
BLE_HR_CHARACTERISTIC_RAW_UUID: Final[str] = "ff241160-8a02-4626-b499-b1572d2b5a29"
async def main():

60
main.py
View File

@ -27,7 +27,7 @@ from pydantic import BaseModel, computed_field
from datetime import datetime, timedelta
import awkward as ak
from awkward import Array as AwkwardArray, Record as AwkwardRecord
from app.model import AlgoReport
from app.model import AlgoReport, HrPacket, hr_confidence_to_num
from app.utils import Instant
from collections import deque
from dataclasses import dataclass
@ -36,7 +36,7 @@ from dataclasses import dataclass
class AppHistory(TypedDict):
timescape: deque[datetime]
hr_data: deque[float]
hr_conf: deque[int] # in %
hr_conf: deque[float] # in %
accel_x_data: deque[int]
accel_y_data: deque[int]
accel_z_data: deque[int]
@ -153,38 +153,28 @@ def main():
message = state["message_queue"].receive_nowait()
except anyio.WouldBlock:
continue
report = AlgoReport.unmarshal(message)
if state["refresh_inst"].mut_every_ms(500):
md_placeholder.markdown(
f"""
- HR: {report.data.hr_f}bpm
- HR CONF: {report.data.hr_conf}%
- ACTIVITY: {report.data.activity_class.name}
- SCD: {report.data.scd_contact_state.name}
"""
)
try:
packet = HrPacket.unmarshal(message)
except ValueError as e:
logger.error(f"bad packet: {e}")
continue
with placeholder.container():
history["timescape"].append(datetime.now())
history["hr_data"].append(report.data.hr_f)
history["hr_conf"].append(report.data.hr_conf)
history["accel_x_data"].append(report.accel_x)
history["accel_y_data"].append(report.accel_y)
history["accel_z_data"].append(report.accel_z)
history["pd_data"].append(report.led_2)
fig_hr, fig_accel, fig_pd = st.tabs(["Heart Rate", "Accelerometer", "PD"])
history["hr_data"].append(packet.hr)
history["hr_conf"].append(hr_confidence_to_num(packet.status.hr_confidence))
history["pd_data"].extend(packet.raw_data)
fig_hr, fig_pd = st.tabs(["Heart Rate", "PD"])
with fig_hr:
st.plotly_chart(
go.Figure(
data=[
go.Scatter(
x=list(history["timescape"]),
y=list(history["hr_data"]),
mode="lines",
name="HR",
),
go.Scatter(
x=list(history["timescape"]),
y=list(history["hr_conf"]),
mode="lines",
name="HR Confidence",
@ -192,37 +182,11 @@ def main():
]
)
)
with fig_accel:
st.plotly_chart(
go.Figure(
data=[
go.Scatter(
x=list(history["timescape"]),
y=list(history["accel_x_data"]),
mode="lines",
name="x",
),
go.Scatter(
x=list(history["timescape"]),
y=list(history["accel_y_data"]),
mode="lines",
name="y",
),
go.Scatter(
x=list(history["timescape"]),
y=list(history["accel_z_data"]),
mode="lines",
name="z",
),
]
)
)
with fig_pd:
st.plotly_chart(
go.Figure(
data=[
go.Scatter(
x=list(history["timescape"]),
y=list(history["pd_data"]),
mode="lines",
name="PD",