Patient transportation assistance and control

A patient transport device, comprising:

• a transport base comprising a plurality of wheels comprising a powered wheel;
• a patient support structure mounted to the transport base;
• a first handle mounted to the patient support structure;
• a second handle mounted to the patient support structure;
• a first force sensor mounted proximate to the first handle and configured to output a first force signal in response to sensing movement of the first handle, the first force signal comprising a first force value;
• a second force sensor mounted proximate to the second handle and configured to output a second force signal in response to sensing movement of the second handle, the second force signal comprising a second force value;
• and
• a distributed control system comprising a system processor and a plurality of subsystem controllers;
• wherein each subsystem controller is configured to control operation of one of a plurality of subsystems of the patient transport device;
• and
• wherein the system processor is configured to:
• monitor and communicate with the plurality of subsystem controllers;
• determine an updated velocity vector, comprising:
• determining a magnitude of the updated velocity vector based on the first force value and the second force value;
• and
• determining a direction of the updated velocity vector based on the first force value, the second force value, a first model, a current velocity of the transport device, and a distance between the first and second handles;
• and
• operate the powered wheel based on the updated velocity vector.

A method for training a machine learning algorithm for generating an updated velocity vector for a patient transport device, the method comprising:

• providing a patient transport device comprising:
• a non-powered, free-wheeling transport base;
• a patient support structure mounted to the transport base;
• a first handle mounted to the patient support structure;
• a second handle mounted to the patient support structure;
• a first force sensor mounted proximate to the first handle and configured to output a first force signal in response to sensing movement of the first handle, the first force signal comprising a first force value;
• a second force sensor mounted proximate to the second handle and configured to output a second force signal in response to sensing movement of the second handle, the second force signal comprising a second force value;
• an inertial measurement unit (IMU);
• and
• a control system comprising a system processor configured to determine a measured current velocity of the patient transport device based on an output signal from the IMU;
• pushing and/or pulling at least one of the first handle and the second handle to move the patient transport device;
• recording multiple instances of the first force value, the second force value, and the measured current velocity to generate training data;
• and
• applying a first machine learning algorithm to the training data to produce a first machine learning model configured to predict a direction of an intended velocity vector corresponding to forces imparted to the first handle and/or the second handle.

A patient transport device, comprising:

• a transport base comprising a plurality of wheels comprising a powered wheel;
• a vertical actuation mechanism comprising a mounting bracket attached to the powered wheel, a drive train engaged with the mounting bracket, and a handle rotatably coupled with the drive train;
• a patient support structure mounted to the transport base;
• a first handle mounted to the patient support structure;
• a second handle mounted to the patient support structure;
• a first force sensor mounted proximate to the first handle and configured to output a first force signal in response to sensing movement of the first handle, the first force signal comprising a first force value;
• a second force sensor mounted proximate to the second handle and configured to output a second force signal in response to sensing movement of the second handle, the second force signal comprising a second force value;
• and
• a control system comprising a system processor configured to:
• determine an updated velocity vector, comprising:
• determining a magnitude of the updated velocity vector based on a sum of the first and second force values;
• and
• determining a direction of the updated velocity vector based on the first force value, the second force value, a first model, a current velocity of the transport device, and a distance between the first and second handles;
• and
• operate the powered wheel based on the updated velocity vector.