B I O M E C H A N I C S W O R K L O A D P R O D U C T S

4-SENSOR GAIT ANALYSIS MODULELICENSED FOR SHOE-FITTING

FIRST WEARABLE APPROVED FORMLB IN-GAME USE (2015)

T E C H N O L O G Y D O M A I N E X P E R T I S E

HIGH-DYNAMICRANGE 6-AXIS IMU

+ FIRMWARE

FULL-BODY BIOMECHANICS PHYSICS ENGINE AND SENSOR

FUSION LIBRARY

NEURAL-NETMOVEMENT CLASS-IFICATION ENGINE

IN-HOME PHYSICAL THERAPYREMOTE KNEE WORKLOAD MONITOR

CLASS 1 MED-ICAL DEVICE

REAL-TIME MOBILE3D VIEWER AND MOVE LIBRARY

FW WL

WORKLOADCOMPUTATION

CLOUD SERVICES

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H A R D W A R E S P E C I F I C AT I O N S

I N D U S T R Y ’ S S M A L L E S TI N E R T I A L S E N S O R

BATTERY LIFE (120 mAh Rechargeable Li-Po)

8 hours for Event Trigger Mode3 hours for Logging Mode4.5 hours for Streaming Mode6 hours Hybrid Event Trigger/Streaming Mode

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DATA SAMPLING MODES

Logging Mode: Programatically log 6-axis data sampled at 1000 Hz.Event Trigger Mode: Stores 5 seconds of 6-axis data sampled at 1000 Hz after event detection algorithm triggers.Streaming Mode: Sample and stream 6-axis data at 100 Hz in “real-time” with 30 ms latency

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6-AXIS INERTIAL MEASUREMENT UNIT (IMU)3-axis Gyroscope: +/- 4000 dps3-axis Accelerometer: +/- 24 g’s

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BLUETOOTH (BLE 4.0, 2.6 kb/s)

4 seconds per Event Trigger30 ms latency for Streaming Mode40 minutes per 2 hour Logging Session

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C U R R E N T F I R M W A R E A R C H I T E C T U R E S

Live Streaming Mode - High Power Consumption

Sends SamplesEvery Connection

Interval (30ms)32 kHz Precision Clock

(20 ppm drift)

BLE FLASH

ACC GYRO

RAM MCU

MCU Samples 6-axisdata plus timestamp at100 Hz, and sends 3-4samples of data to perhipheral every 30ms.

100 HzOccassional Usage

of BLE & Flash

Sensor1

Sensor2

t = 0.0 s t = 20 minutes

Accurately/time-synced sensor data received by phone after each sample.

Sens

or 1

Dat

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nsor

2 D

ata

Program Trigger Mode - Moderate Power Consumption

1 kHz Clock (Large Drift)

Clock Triggers x3Every 10 minutes

BLE FLASH

ACC GYRO

RAM MCUStore 5 seconds of data from RAM toFLASH upon trigger

Event Triggert = 4.0 s

t = 0.0 s t = 5.0 s

Programatically TriggerBased on Timer orEvent Detection Algorithms

Intermittent FLASHUsage

t = 0.0 s t = 16.0 s

t = 16.8 s

Resize toknown time

t = 0.0 s t = 16.0 s

t = 16.8 s

Resize toknown time

10 Minute Gap

Phone Trigger Mode - High Power Consumption

1 kHz Clock (Large Drift)Event Trigger

ACC GYRO

BLE FLASH RAM MCUStore 5 seconds of data from RAM toFLASH upon trigger

Event Triggert = 4.0 s

t = 0.0 s t = 5.0 s

t = 0.0 st = 16.0 s

t = 16.8 s

Resize toknown time

B I O M E C H A N I C S D ATA O U T P U T

SENSOR FUSION OUTPUTSensor Linear Acceleration, Velocity, Position (XYZ)Sensor Angular Acceleration, Velocity, Orientation (XYZ, Euler Angles)

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TRANSLATED KINEMATICSObject Velocity (i.e. ball, racket, hand)Joint Kinetics (i.e. Flexion Torque, Valgus Torque, etc.)

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MULTI-SENSOR JOINT KINEMATICSUpper Extremity: Elbow Flexion, Shoulder Internal/Ex-ternal Rotation, Abduction, Flexion/Extension.Pelvis/Torso: Flexion/Extension, Lateral Flexion, Rota-tionHip: Flexion/Extension, Internal/External Rotation, Ab/AdductionKnee/Ankle: Flexion

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KEY FRAME IDENTIFICATIONPoint of Contact (i.e. ball release, ball contact)Point of Movement Initiation (i.e. load, peak back-swing).Local/Global Maximum/Minimum Detection

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W O R K L O A D C L O U D S E R V I C E S

WORKLOAD MEASURESDaily Workload (Exponential sum of Torque, Veloc-ity, etc.)Acute Workload: Rolling 7 day average of daily workloadChronic Workload: Rolling 28 day average of daily workloadAcute:chronic Ratio (ACR): Acute workload divided by chronic workload

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WORKLOAD SIMULATORProject 28-days of future workloads that increase chronic workload and limit high ACR exposure.Designate pre-game warmup workload routines.Simulate game-day workload and effect on ACR.Auto-generate workload limits on game-dayConvert game-day workload limits to actionable activity limits (after warmup workloads are sub-tracted).

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C U R R E N T P H Y S I C S E N G I N E A R C H I T E C T U R E

x,y,z Acc

x,y,z Gyro

x,y,z Acc

x,y,z Gyro

SENSOR FUSION& CALIBRATION

INVERSE DYNAMICSPHYSICS ENGINE

ELBOW VALGUS TORQUEEVENT DETECTION

FULL SAMPLING

ELBOW TORQUE WORKFLOW

P R O P O S E D A R C H I T E C T U R E

ELBOW TORQUE WORKFLOW

1 Capture Baseline of Full-Sampled Data 2 Train Neural Net for Torque w/ Sensor Data

STANDARD PROGRAM TRIGGER FW VIA TENSORFLOW INTEGRATION

3 Load Player-Specific Models on New FW

Requires FW re-write to handle flash memory blocks and peak detection after event detection.Requires creation of integer based math (not float).Requires creation of BLE Characteristic of count, peak torque, and arrays for APEX compatability

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NEURAL NETWORK TRAINING OF ELBOW TORQUE

PRO

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E X PA N D E D P R O O F O F C O N C E P T

FIRMWARE BIOS/MCU CONTROLLER

PRE-

LOAD

ED N

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LN

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Metadata6-axis 1 KHz

Rep Counting

Metrics (velocity, etc)

3D View Data

User IDSession Data

MOTUSSERVER

Workload Calculations

Workload Prescriptions

Advanced Analytics

MOTUS SENSOR

APEX SENSOR

FIRMWARE BIOS/MCU CONTROLLER

3-AX

ISAC

CEL.

IMU

/GPS

ON

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ARD

PYSI

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BLU

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LE 4

.0Peak Torque & TimestampBLE Characteristics

SENSOR FUSION& CALIBRATION

INVERSE DYNAMICSPHYSICS ENGINE

Workload Display

MOTUS POST SESSIONiOS APP

BLE SMARTWATCH

Rep Counting

Workload Display

Prescription Compare

STATSPORTSWIFI BEACONS

STATSPORTSREAL TIME IPAD APP

STATSPORTSSERVER

Workload Calculations

Workload Prescriptions

Advanced Analytics

Workload Prescriptions

Neural NetWeights

DATATX/RX

DATATX/RX

User IDSession Data

Workload Prescriptions

WorkloadPrescriptions

STATSPORTS DATA

MOTUSWEB-DASH

SONRAWEB-DASH