Method and system for human-computer interaction performance evaluation based on virtual reality

A computer-implemented method for human-computer interaction performance evaluation based on virtual reality, comprising:

• collecting and analyzing human-computer interaction data from a human-computer interaction system:
• in a virtual reality environment, controlling a user to execute an interaction task through a human-computer interaction device, collecting and analyzing behavioral data of the user during task execution, collecting and analyzing interaction data of the human-computer interaction device during task control, and deriving a user behavior interaction index and a device interaction performance index;
• evaluating human-computer interaction performance:
• analyzing the user behavior interaction index and the device interaction performance index to obtain a human-computer interaction performance evaluation indicator;
• optimizing the human-computer interaction:
• comparing and matching the human-computer interaction performance evaluation indicator with a preset human-computer interaction performance evaluation indicator, to obtain a human-computer interaction performance optimization solution, and finally optimizing the human-computer interaction system based on the human-computer interaction performance optimization solution to improve the human-computer interaction performance of the human-computer interaction device;
• wherein the human-computer interaction system is a system software of the human-computer interaction device;
• the user behavior interaction index is analyzed as follows:
• interaction efficiency of the user during task execution, a maximum heart rate of the user during task execution, and an average respiratory rate of the user during task execution are analyzed to obtain the user behavior interaction index, with an analysis formula as follows:
• ρ
• =
• ❘
• "\[LeftBracketingBar]"
• yt
• -
• Δ
• ⁢
• yt
• ❘
• "\[RightBracketingBar]"
• Δ
• ⁢
• y
• ⁢
• t
• *
• x
• 1
• +
• ❘
• "\[LeftBracketingBar]"
• yo
• -
• Δ
• ⁢
• yo
• ❘
• "\[RightBracketingBar]"
• Δ
• ⁢
• y
• ⁢
• o
• *
• x
• 2
• +
• ❘
• "\[LeftBracketingBar]"
• yh
• -
• Δ
• ⁢
• yh
• ❘
• "\[RightBracketingBar]"
• Δ
• ⁢
• y
• ⁢
• h
• *
• x
• 3
• +
• 1
• ;
• in the formula, ρ is a user behavior interaction index, yt represents interaction efficiency of the user during task execution, Δyt represents reference interaction efficiency preset in an interaction database, x1 is a correction factor corresponding to the interaction efficiency preset in the interaction database, yo is a maximum heart rate of the user during task execution, Δyo is a reference heart rate preset in the interaction database, x2 is a correction factor corresponding to the reference heart rate of the user preset in the interaction database, yh is an average respiratory rate of the user during task execution, Δyh is an average reference respiratory rate of the user preset in the interaction database, and x3 is a correction factor corresponding to the reference respiratory rate of the user preset in the interaction database;
• an interaction task execution completion duration, an interaction task execution accuracy rate, and an interaction task execution time accuracy rate are processed to obtain the device interaction performance index, with an analysis formula as follows:
• d
• ⁢
• i
• =
• l
• ⁢
• g
• ⁡
• (
• ❘
• "\[LeftBracketingBar]"
• dt
• -
• Δ
• ⁢
• dt
• ❘
• "\[RightBracketingBar]"
• Δ
• ⁢
• d
• ⁢
• t
• *
• h
• 1
• +
• ❘
• "\[LeftBracketingBar]"
• dr
• -
• Δ
• ⁢
• dr
• ❘
• "\[RightBracketingBar]"
• Δ
• ⁢
• dr
• *
• h
• 2
• +
• ❘
• "\[LeftBracketingBar]"
• dp
• -
• Δ
• ⁢
• dp
• ❘
• "\[RightBracketingBar]"
• Δ
• ⁢
• d
• ⁢
• p
• *
• h
• 3
• +
• 1
• )
• ;
• in the formula, di is a device interaction performance index, dt represents an interaction task execution completion duration, Δdt represents a reference interaction task execution completion duration preset in the interaction database, h1 is a correction factor corresponding to the interaction task execution completion duration preset in the interaction database, dr represents an interaction task execution accuracy rate, Δdr represents a reference interaction task execution accuracy rate preset in the interaction database, h2 is a correction factor corresponding to the interaction task execution accuracy rate preset in the interaction database, dp is an interaction task execution time accuracy rate, Δdp represents a reference interaction task execution time accuracy rate preset in the interaction database, and h3 is a correction factor corresponding to the interaction task execution time accuracy rate preset in the interaction database;
• the human-computer interaction performance evaluation indicator is analyzed as follows:
• the user behavior interaction index and the device interaction performance index are analyzed to obtain the human-computer interaction performance evaluation indicator, with a specific analysis formula as follows:
• ∂
• =
• e
• ρ
• *
• m
• 1
• +
• e
• d
• ⁢
• i
• *
• m
• 2
• e
• ;
• in the formula, ∂ is a human-computer interaction performance evaluation indicator, e is a natural constant, ρ is a user behavior interaction index, m1 is a weight factor corresponding to the user behavior interaction index preset in an interaction database, di is a device interaction performance index, and m2 is a weight factor corresponding to the device interaction performance index preset in the interaction database.