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Identify abnormally elevated T waves as R waves #108
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20230825_211455.zip The following is the file reading function healthMap = open(self.healthFilePath, 'rb')
healthMap.read(68)
healthMap.read(6)
healthMap.read(2)
self.SN = healthMap.read(18).decode()
print(f"设备序列号:{self.SN}")
healthMap.read(102)
self.Ver = healthMap.read(11).decode()
print(f"设备版本号:{self.Ver}")
healthMap.read(49)
self.startTime = int.from_bytes(healthMap.read(4), byteorder='little', signed=False)
self.endTime = int.from_bytes(healthMap.read(4), byteorder='little', signed=False)
print(f"start time:{self.startTime}\nend time:{self.endTime}")
healthMap.read(236)
while True:
# 每个数据点2字节
# 2 byte == 1 data point
data = healthMap.read(2)
if data == b'':break
# 复位电压零点 12位AD值最大4096
# 2048 == 0mV
data = int.from_bytes(data, byteorder='little', signed=False)-2048
data *= 0.00125 # Estimate sampling points and voltage values 估算的采样点与电压值
self.healthMapList.append(data)
self.healthMapLenth = len(self.healthMapList)
print(f"数据点数目: {len(self.healthMapList)} 个")
print(f"数据持续时间: {len(self.healthMapList)/500} s")
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figure 1 is hp.process() function
图1是hp.process()函数处理后的图表
figure 2 is partial enlarged figure1
图2是局部放大的图1
figure 3 is Distribution of R-R interval (ibi) in time
图3是R-R间期(心跳间隔 Inter-Beat Interval IBI)在时间上的分布
figure 4 is hp.plot_poincare() function.
图4是hp.plot_poincare()函数直接生成
Can abnormal T waves be filtered?
能否过滤异常T波?
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