Bed having features for automatic sensing of illness states such as post-acute sequalae of covid-19 (pasc or long covid)

A system for classifying a sleeper on a bed into an illness state, the system comprising:

• a bed having a mattress;
• one or more sensors configured to:
• sense one or more physical phenomena of a sleeper on the bed;
• generate data signals based on the sensed physical phenomena;
• and
• send, to a computing system, the data signals;
• the computing system comprising one or more processors and computer memory, the computing system configured to:
• receive the data signals;
• generate, from data signals of a sleep-session of the sleeper, a feature vector of features, each feature having a feature value that represents one of the physical phenomena, wherein the feature vector comprises four features, the four features being:
• sleep duration, breathing rate, gross-body motion, and heart rate;
• and
• classify the sleeper into an illness state of a chronic condition for the sleep session based on the feature vector.

A computer system for classifying a subject based on sensor data, the computer system comprising:

• one or more processors;
• and
• memory storing instructions that, when executed by the processors, cause the processors to perform operations comprising:
• accessing sensor data of a subject that records physiological measures of the subject in at least one sleep session;
• determining, based on the sensor data, the subject has at least a threshold probability of being positive for COVID-19;
• scheduling in the future a determination for the user to determine if the user is begins to demonstrate symptoms of long COVID;
• and
• latter, according to the scheduling, determine if the user has begins to demonstrate symptoms of long COVID.

A computer system for analysis of a progression for long COVID, computer system comprising:

• one or more processors;
• and
• memory storing instructions that, when executed by the processors, cause the processors to perform operations comprising:
• periodically:
• accessing sensor data of a subject that records physiological measures of the subject in at least one sleep session;
• and
• determining, based on the sensor data, a new intensity value of long COVID for the subject;
• adding the new intensity value of long COVID for the subject to a collection of intensity values of long COVID for the subject;
• and
• determining, based on the collection of intensity values of long COVID for the subject, changes in the intensity values of long COVID for the subject.