SYSTEM AND METHOD FOR PERSONALIZED EXERCISE TRAINING AND COACHING
A system and method that includes collecting kinematic data at an activity monitoring system coupled to a user; selecting a training activity of the user, the training activity selected from a plurality of training activity options; and processing the kinematic data in a processing mode of the selected training activity and thereby generating a set of training metrics that comprises at least one training metric.
1 . A method comprising:
collecting kinematic data at an activity monitoring system coupled to a user;
selecting a training activity of the user, the training activity selected from a plurality of training activity options; and
processing the kinematic data in a processing mode of the selected training activity and thereby generating a set of training metrics that comprises at least one training metric.
2 . The method of claim 1 , wherein the plurality of training activity options comprises at least pushups, lunges, squats, and planks.
3 . The method of claim 2 , wherein the plurality of training activity options further comprises at least bicep curls, deadlifting, jumping jacks, sit ups, and pull ups.
4 . The method of claim 1 , wherein the plurality of training activity options comprises at least pushups.
5 . The method of claim 4 , wherein processing the kinematic data further comprises processing in a pushup processing mode that comprises of segmenting pushup repetitions from the kinematic data and extracting push training metrics from pushup repetitions.
6 . The method of claim 5 , wherein processing in a pushup processing mode further comprises detecting a style of pushups from a set of pushup styles.
7 . The method of claim 1 , wherein the plurality of training activity options comprises at least lunges; and wherein processing the kinematic data further comprises processing in a lunge processing mode that comprises classifying lunge foot, counting lunges by foot, and classifying at least one aspect of lunge form.
8 . The method of claim 1 , wherein the plurality of training activity options comprises at least squats; and wherein processing the kinematic data further comprises processing in a squat processing mode that comprises counting squats and classifying at least one aspect of squat form.
9 . The method of claim 1 , wherein the plurality of training activity options comprises at least planks; and wherein processing the kinematic data further comprises processing in a plank processing mode that comprises generating the training metrics of plank duration, pelvic tilt, core stability, and plank style classification.
10 . The method of claim 1 , wherein the plurality of training activity options comprises at least one asymmetric training activity; and wherein processing the kinematic data comprises, in an asymmetric processing mode, detecting training activity side through the kinematic data and generating training metrics for right and left sides of a training activity.
11 . The method of claim 10 , further comprising generating a comparison of training metrics of the left and right sides of a training activity.
12 . The method of claim 1 , wherein selecting a training activity of the user, further comprises processing the kinematic data in a classification mode and thereby identifying a current training activity.
13 . The method of claim 1 , further comprising monitoring the training metrics compared to at least one training condition and generating feedback.
14 . The method of claim 1 , further comprising generating an exercise plan from the training metrics.
15 . The method of claim 1 , wherein processing of the kinematic data and generating at least one training metric comprises classifying form of performing a training activity through the kinematic data.
16 . The method of claim 1 , wherein processing of the kinematic data and generating at least one training metric comprises detecting a fatigue state in kinematic data during performance of a training activity.
17 . The method of claim 1 , further comprising collecting an electromyography signal from the user, predicting muscle usage from the electromyography signal during a training activity, and generating a form classification training metric classifying on muscle usage and at least a subset of the training metrics of the training activity.
18 . A system comprising:
an inertial measurement unit configured to collect kinematic data when coupled to a user;
a processing system configured to:
select a training activity from a plurality of training activity options, and
process the kinematic data in a processing mode of the selected training activity and thereby generate a set of training metrics.
19 . The system of claim 18 , wherein the plurality of training activity options comprises at least pushups, lunges, squats, and planks.
20 . The system of claim 18 , further comprising at least one feedback interface activated in response to the training metrics.