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SENS motion - Discrete Wearable Activity Sensor for Healthcare and Research

Behandling af rå accelerometerdata

Background
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Denne artikel indeholder eksempler på den indledende loading af rå accelerometerdata til RStudio eller Python. Begge eksempler behandler en .bin fil.

For at eksportere en .bin fil, se denne artikel.

RStudio
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Herunder ses et eksempel-script i RStudio til at importere og organisere accelerometerdata.

R Script 
file_path <- "export_1_acc.bin"

# Record layout (bytes)
TIMESTAMP_BYTES <- 6
AXIS_BYTES      <- 2
RECORD_SIZE     <- TIMESTAMP_BYTES + 3 * AXIS_BYTES

# ---- READ BINARY FILE ----
file_size <- file.info(file_path)$size
if (file_size %% RECORD_SIZE != 0) {
  stop("File size is not a multiple of record size.")
}
con <- file(file_path, "rb")
raw_data <- readBin(con, what = "raw", n = file_size)
close(con)

# Arrange raw bytes into records
data_matrix <- matrix(raw_data, ncol = RECORD_SIZE, byrow = TRUE)

# ---- TIMESTAMP CONVERSION ----
# Convert 6-byte big-endian timestamp (ms since Unix epoch)
convert_timestamp <- function(bytes) {
  sum(as.integer(bytes) * 256^(rev(seq_along(bytes)) - 1))
}
timestamps_numeric <- apply(data_matrix[, 1:TIMESTAMP_BYTES], 1, convert_timestamp)
timestamps <- as.POSIXct(timestamps_numeric / 1000, origin = "1970-01-01", tz = "GMT")

# ---- SENSOR AXES ----
decode_axis <- function(mat, scale = 0.0078125) {
  readBin(as.raw(t(mat)), what = "integer", size = 2, signed = TRUE, endian = "big", n = nrow(mat)) * scale
}

x <- decode_axis(data_matrix[,  7:8])
y <- decode_axis(data_matrix[,  9:10])
z <- decode_axis(data_matrix[, 11:12])

# ---- FINAL DATA FRAME ----
df_final <- data.frame(time = timestamps, x = x, y = y, z = z)
write.csv(df_final, "cleaned_data_2.csv", row.names = FALSE)

Python
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Denne Python function læser en .bin fil og gemmer det i et NumPy array med 4 kolonner. Kolonne 0 er timestamp, kolonne 1-3 er x, y, z. X, y og z skaleres med 0.0078125 G.

Python Function 
    def read_bin_file(self, filename):
        s = struct.Struct('>qhhh')
        sz = os.path.getsize(filename)
        data = numpy.zeros([int(sz/12), 4])
        i = 0
        f = open(filename, 'rb')
        while True:
            d = f.read(12)
            if len(d) == 0:
                break
            data[i, :] = s.unpack(b'\0\0' + d)
            #ts, x, y, z = s.unpack(b'\0\0' + d)
            i += 1
        return data