{
 "model": "pace-cnn",
 "version": "0.1.0",
 "format": "pace-cnn-v1",
 "labels": [
  "walking",
  "walking_upstairs",
  "walking_downstairs",
  "sitting",
  "standing",
  "laying"
 ],
 "input": {
  "shape": [
   1,
   128,
   9
  ],
  "layout": "row-major: sample t, then channel c (index t * 9 + c)",
  "window": 128,
  "rate_hz": 50,
  "overlap": 0.5,
  "channels": [
   {
    "name": "body_acc_x",
    "unit": "g (1 g = 9.80665 m/s^2)"
   },
   {
    "name": "body_acc_y",
    "unit": "g (1 g = 9.80665 m/s^2)"
   },
   {
    "name": "body_acc_z",
    "unit": "g (1 g = 9.80665 m/s^2)"
   },
   {
    "name": "body_gyro_x",
    "unit": "rad/s"
   },
   {
    "name": "body_gyro_y",
    "unit": "rad/s"
   },
   {
    "name": "body_gyro_z",
    "unit": "rad/s"
   },
   {
    "name": "total_acc_x",
    "unit": "g (1 g = 9.80665 m/s^2)"
   },
   {
    "name": "total_acc_y",
    "unit": "g (1 g = 9.80665 m/s^2)"
   },
   {
    "name": "total_acc_z",
    "unit": "g (1 g = 9.80665 m/s^2)"
   }
  ],
  "sensor": "6-axis IMU worn at the waist (belt), as in UCI HAR"
 },
 "normalisation": {
  "rule": "(x - mean) / std per channel",
  "from": "training subjects of uci-har-v1 (validation excluded)",
  "mean": [
   -0.0004951871815137565,
   -0.00032817694591358304,
   -0.00021286075934767723,
   0.0005902921548113227,
   -0.0004714796377811581,
   -0.00026790332049131393,
   0.8028175234794617,
   0.02752470225095749,
   0.081498883664608
  ],
  "std": [
   0.19266846776008606,
   0.1205918937921524,
   0.10867609083652496,
   0.4066708981990814,
   0.3769063949584961,
   0.25676658749580383,
   0.410501092672348,
   0.382828027009964,
   0.373470276594162
  ]
 },
 "quantisation": {
  "input_scale": 0.060373175889253616,
  "input_zero_point": -1,
  "output_scale": 0.06330011039972305,
  "output_zero_point": -19,
  "output": "int8 scores in label order; argmax is the predicted activity"
 },
 "preparation": {
  "rate_hz": 50,
  "window": 128,
  "step": 64,
  "units": {
   "acc": "g (1 g = 9.80665 m/s^2)",
   "gyro": "rad/s"
  },
  "channels": [
   "body_acc_x",
   "body_acc_y",
   "body_acc_z",
   "body_gyro_x",
   "body_gyro_y",
   "body_gyro_z",
   "total_acc_x",
   "total_acc_y",
   "total_acc_z"
  ],
  "steps": [
   {
    "op": "median",
    "length": 3,
    "causal": true,
    "on": "acc and gyro, per axis"
   },
   {
    "op": "butterworth_lowpass",
    "order": 3,
    "cutoff_hz": 20.0,
    "on": "acc and gyro, per axis",
    "sos": [
     [
      0.6990599365895495,
      1.398119873179099,
      0.6990599365895495,
      1.0,
      1.25051643084874,
      0.5457233155094577
     ],
     [
      0.7547627247472144,
      0.7547627247472144,
      0.0,
      1.0,
      0.5095254494944288,
      0.0
     ]
    ]
   },
   {
    "op": "gravity_separation",
    "lowpass": {
     "type": "butterworth",
     "order": 3,
     "cutoff_hz": 0.3,
     "sos": [
      [
       0.0003486925369977911,
       0.0006973850739955822,
       0.0003486925369977911,
       1.0,
       -1.9616121845004821,
       0.9630069546484733
      ],
      [
       0.0185029745248923,
       0.0185029745248923,
       0.0,
       1.0,
       -0.9629940509502154,
       0.0
      ]
     ]
    },
    "body_acc": "total_acc - lowpass(total_acc)"
   },
   {
    "op": "normalise",
    "rule": "(x - mean) / std per channel, training-subject constants"
   },
   {
    "op": "quantise",
    "rule": "round(x / input_scale) + input_zp, clipped to int8"
   }
  ],
  "filter_form": "second-order sections, transposed direct form II, causal; state starts at the steady state of the first sample",
  "chosen_by_the_zoo": [
   "median length 3",
   "gravity filter order 3",
   "causal filtering"
  ]
 },
 "benchmark": "uci-har-v1"
}