Clarification of question intent
It sounds like what you want is the acceleration of your device with respect to your laptop. As you correctly mentioned, the similar question Acceleration from device's coordinate system into absolute coordinate system maps the local accelerometer data of a device with respect to a global frame of reference (FoR) (the Cartesian "flat" Earth FoR to be specific - as opposed to the ultra-realistic spherical Earth FoR).
What you know
From your device, you know the local Phone FoR, and from the link above, you can also find the behavior of your device with respect to a flat Earth FoR with a rotation matrix, which I'll call R_EP for Rotation in Earth FoR from Phone FoR. In order to represent the acceleration of your device with respect to your laptop, you will need to know how your laptop is oriented and positioned with respect to either your phone's FoR (A), or the flat Earth FoR (B), or some other FoR that is known to both your laptop and your phone but I'll ignore this cause it's irrelevant and the method is identical to B.
What you'll need
In the first case, A, this will allow you to construct a rotation matrix which I'll call R_LP for Rotation in Laptop FoR from Phone FoR - and that would be super convenient because that's your answer. But alas, life isn't fun without a little bit of a challenge.
In the second case, B, this will allow you to construct a rotation matrix which I'll call R_LE for Rotation in Laptop FoR from Earth FoR. Because the Hamilton product is associative (but NOT commutative: Are quaternions generally multiplied in an order opposite to matrices?), you can find the acceleration of your phone with respect to your laptop by daisy-chaining the rotations, like so:
a_P]L = R_LE * R_EP * a_P]P
Where the ] means "in the frame of", and a_P is acceleration of the Phone. So a_P]L is the acceleration of the Phone in the Laptop FoR, and a_P]P is the acceleration of the Phone in the Phone's FoR.
NOTE When "daisy-chaining" rotation matrices, it's important that they follow a specific order. Always make sure that the rotation matrices are multiplied in the correct order, see Sections 2.6 and 3.1.4 in [1] for more information.
Hint
To define your laptop's FoR (orientation and position) with respect to the global "flat" Earth FoR, you can place your phone on your laptop and set the current orientation and position as your laptop's FoR. This will let you construct R_LE.
Misconceptions
A rotation quaternion, q, is NEITHER the orientation NOR attitude of one frame of reference relative to another. Instead, it represents a "midpoint" vector normal to the rotation plane about which vectors from one frame of reference are rotated to the other. This is why defining quaternions to rotate from a GLOBAL frame to a local frame (or vice-versa) is incredibly important. The ENU to NED rotation is a perfect example, where the rotation quaternion is [0; sqrt(2)/2; sqrt(2)/2; 0], a "midpoint" between the two abscissa (X) axes (in both the global and local frames of reference). If you do the "right hand rule" with your three fingers pointing along the ENU orientation, and rapidly switch back and forth from the NED orientation, you'll see that the rotation from both FoR's is simply a rotation about [1; 1; 0] in the Global FoR.
References
I cannot recommend the following open-source reference highly enough:
[1] "Quaternion kinematics for the error-state Kalman filter" by Joan Solà. https://hal.archives-ouvertes.fr/hal-01122406v5
For a "playground" to experiment with, and gain a "hands-on" understanding of quaternions:
[2] Visualizing quaternions, An explorable video series. Lessons by Grant Sanderson. Technology by Ben Eater https://eater.net/quaternions
